diff --git a/layerNormedGRU.py b/layerNormedGRU.py
new file mode 100644
index 0000000..1010836
--- /dev/null
+++ b/layerNormedGRU.py
@@ -0,0 +1,78 @@
+import numpy as np
+import tensorflow as tf
+
+
+class layerNormedGRU(tf.contrib.rnn.RNNCell):
+
+  def __init__(
+      self, size, activation=tf.tanh, reuse=None,
+      normalizer=tf.contrib.layers.layer_norm,
+      initializer=tf.contrib.layers.xavier_initializer()):
+    super(layerNormedGRU, self).__init__(_reuse=reuse)
+    self._size = size
+    self._activation = activation
+    self._normalizer = normalizer
+    self._initializer = initializer
+
+  @property
+  def state_size(self):
+    return self._size
+
+  @property
+  def output_size(self):
+    return self._size
+
+  def call(self, input_, state):
+    update, reset = tf.split(self._forward(
+        'update_reset', [state, input_], 2 * self._size, tf.nn.sigmoid,
+        bias_initializer=tf.constant_initializer(-1.)), 2, 1)
+    candidate = self._forward(
+        'candidate', [reset * state, input_], self._size, self._activation)
+    state = (1 - update) * state + update * candidate
+    return state, state
+
+  def _forward(self, name, inputs, size, activation, **kwargs):
+    with tf.variable_scope(name):
+      return _forward(
+          inputs, size, activation, normalizer=self._normalizer,
+          weight_initializer=self._initializer, **kwargs)
+
+
+def _forward(
+    inputs, size, activation, normalizer=tf.contrib.layers.layer_norm,
+    weight_initializer=tf.contrib.layers.xavier_initializer(),
+    bias_initializer=tf.zeros_initializer()):
+  if not isinstance(inputs, (tuple, list)):
+    inputs = (inputs,)
+  shapes = []
+  outputs = []
+  # Map each input to individually normalize their outputs.
+  for index, input_ in enumerate(inputs):
+    shapes.append(input_.shape[1: -1].as_list())
+    input_ = tf.contrib.layers.flatten(input_)
+    weight = tf.get_variable(
+        'weight_{}'.format(index + 1), (int(input_.shape[1]), size),
+        tf.float32, weight_initializer)
+    output = tf.matmul(input_, weight)
+    if normalizer:
+      output = normalizer(output)
+    outputs.append(output)
+  output = tf.reduce_mean(outputs, 0)
+  # Add bias after normalization.
+  bias = tf.get_variable(
+      'weight', (size,), tf.float32, bias_initializer)
+  output += bias
+  # Activation function.
+  if activation:
+    output = activation(output)
+  # Restore shape dimensions that are consistent among inputs.
+  min_dim = min(len(shape[1:]) for shape in shapes)
+  dim_shapes = [[shape[dim] for shape in shapes] for dim in range(min_dim)]
+  matching_dims = ''.join('NY'[len(set(x)) == 1] for x in dim_shapes) + 'N'
+  agreement = matching_dims.index('N')
+  remaining = sum(np.prod(shape[agreement:]) for shape in shapes)
+  if agreement:
+    batch_size = output.shape[0].value or -1
+    shape = [batch_size] + shapes[:agreement] + [remaining]
+    output = tf.reshape(output, shape)
+  return output
diff --git a/model901.py b/model901.py
new file mode 100644
index 0000000..9467734
--- /dev/null
+++ b/model901.py
@@ -0,0 +1,87 @@
+import tensorflow as tf
+import numpy as np
+from layerNormedGRU import layerNormedGRU
+
+class model:
+
+    def __init__(self, num_class, topk_paths = 10):
+        self.xs = tf.placeholder(tf.float32, [None, 1000, 161])
+        self.ys = tf.sparse_placeholder(tf.int32)
+        self.learning_rate = tf.placeholder(tf.float32)
+        self.seq_len = tf.placeholder(tf.int32, [None])
+        self.isTrain = tf.placeholder(tf.bool, name='phase')
+
+        xs_input = tf.expand_dims(self.xs, 3)
+
+        conv1 = self._nn_conv_bn_layer(xs_input, 'conv_1', [11, 41, 1, 32], [3, 2])
+        conv2 = self._nn_conv_bn_layer(conv1, 'conv_2', [11, 21, 32, 32], [1, 2])
+        conv_out = tf.reshape(conv2, [-1, 334, 41*32])
+        biRNN1 = self._biRNN_bn_layer(conv_out, 'biRNN_1', 256)
+        biRNN2 = self._biRNN_bn_layer(biRNN1, 'biRNN_2', 256)
+        biRNN3 = self._biRNN_bn_layer(biRNN2, 'biRNN_3', 256)
+
+        self.phonemes = tf.layers.dense(biRNN3, num_class)
+
+        # Notes: tf.nn.ctc_loss performs the softmax operation for you, so
+        # inputs should be e.g. linear projections of outputs by an LSTM.
+        self.loss = tf.reduce_mean(tf.nn.ctc_loss(labels=self.ys, inputs=self.phonemes, sequence_length=self.seq_len,
+                                                  ignore_longer_outputs_than_inputs=True, time_major=False))
+
+        optimizer = tf.train.AdamOptimizer(self.learning_rate, beta1 = 0.6, beta2 = 0.8)
+        update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
+        with tf.control_dependencies(update_ops):
+            gvs = optimizer.compute_gradients(self.loss)
+            capped_gvs = [(tf.clip_by_value(grad, -400., 400.), var) for grad, var in gvs if grad is not None]
+            self.train_op = optimizer.apply_gradients(capped_gvs)
+
+        self.prediction, log_prob = tf.nn.ctc_beam_search_decoder(tf.transpose(self.phonemes,[1,0,2]), self.seq_len, top_paths=topk_paths, merge_repeated=False)
+
+        self.loss_summary = tf.summary.scalar("loss", self.loss)
+        self.merged = tf.summary.merge_all()
+
+    def _nn_conv_bn_layer(self, inputs, scope, shape, strides):
+        with tf.variable_scope(scope):
+            W_conv = tf.get_variable("W", shape=shape, initializer=tf.contrib.layers.xavier_initializer())
+            h_conv = tf.nn.conv2d(inputs, W_conv, strides=[1, strides[0], strides[1], 1], padding='SAME', name="conv2d")
+            b = tf.get_variable("bias" , shape=[shape[3]], initializer=tf.contrib.layers.xavier_initializer())
+            h_bn = tf.layers.batch_normalization(h_conv+b, training = self.isTrain)
+            h_relu = tf.nn.relu6(h_bn, name="relu6")
+            return h_relu
+
+    def _biRNN_bn_layer(self, input, scope, hidden_units, cell = "LayerNormedGRU"):
+        with tf.variable_scope(scope):
+            if cell == 'GRU':
+                fw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LSTM':
+                fw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'vanila':
+                fw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LayerNormedGRU':
+                with tf.variable_scope('fw_cell'):
+                    fw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+                with tf.variable_scope('bw_cell'):
+                    bw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+            else:
+                raise ValueError("Invalid cell type: "+str(cell))
+
+            (output_fw, output_bw), _ = tf.nn.bidirectional_dynamic_rnn(fw_cell, bw_cell, input, dtype=tf.float32, scope="bi_dynamic_rnn")
+            # output_fw_bn = tf.layers.batch_normalization(output_fw, training = self.isTrain, name = 'output_fw_bn')
+            # output_bw_bn = tf.layers.batch_normalization(output_bw, training = self.isTrain, name = 'output_bw_bn')
+            # bilstm_outputs_concat_1 = tf.concat([output_fw_bn, output_bw_bn], 2)
+            bilstm_outputs_concat_1 = tf.concat([output_fw, output_bw], 2)
+            return bilstm_outputs_concat_1
+
+    def train(self, sess, learning_rate, xs, ys):
+        _, loss, summary = sess.run([self.train_op, self.loss, self.merged], feed_dict = {self.isTrain: True, self.learning_rate: learning_rate, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss, summary
+
+    def get_loss(self, sess, xs, ys):
+        loss = sess.run(self.loss, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss
+
+    def predict(self, sess, xs):
+        prediction = sess.run(self.prediction, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs})
+        return prediction
diff --git a/model902.py b/model902.py
new file mode 100644
index 0000000..a903206
--- /dev/null
+++ b/model902.py
@@ -0,0 +1,89 @@
+import tensorflow as tf
+import numpy as np
+from layerNormedGRU import layerNormedGRU
+
+class model:
+
+    def __init__(self, num_class, topk_paths = 10):
+        self.xs = tf.placeholder(tf.float32, [None, 1000, 161])
+        self.ys = tf.sparse_placeholder(tf.int32)
+        self.learning_rate = tf.placeholder(tf.float32)
+        self.seq_len = tf.placeholder(tf.int32, [None])
+        self.isTrain = tf.placeholder(tf.bool, name='phase')
+
+        xs_input = tf.expand_dims(self.xs, 3)
+
+        conv1 = self._nn_conv_bn_layer(xs_input, 'conv_1', [11, 41, 1, 32], [3, 2])
+        conv2 = self._nn_conv_bn_layer(conv1, 'conv_2', [11, 21, 32, 64], [1, 2])
+        conv_out = tf.reshape(conv2, [-1, 334, 41*64])
+        biRNN1 = self._biRNN_bn_layer(conv_out, 'biRNN_1', 256)
+        biRNN2 = self._biRNN_bn_layer(biRNN1, 'biRNN_2', 256)
+        biRNN3 = self._biRNN_bn_layer(biRNN2, 'biRNN_3', 256)
+        biRNN4 = self._biRNN_bn_layer(biRNN3, 'biRNN_4', 256)
+        biRNN5 = self._biRNN_bn_layer(biRNN4, 'biRNN_5', 256)
+
+        self.phonemes = tf.layers.dense(biRNN5, num_class)
+
+        # Notes: tf.nn.ctc_loss performs the softmax operation for you, so
+        # inputs should be e.g. linear projections of outputs by an LSTM.
+        self.loss = tf.reduce_mean(tf.nn.ctc_loss(labels=self.ys, inputs=self.phonemes, sequence_length=self.seq_len,
+                                                  ignore_longer_outputs_than_inputs=True, time_major=False))
+
+        optimizer = tf.train.AdamOptimizer(self.learning_rate, beta1=0.7, beta2=0.9)
+        update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
+        with tf.control_dependencies(update_ops):
+            gvs = optimizer.compute_gradients(self.loss)
+            capped_gvs = [(tf.clip_by_value(grad, -400., 400.), var) for grad, var in gvs if grad is not None]
+            self.train_op = optimizer.apply_gradients(capped_gvs)
+
+        self.prediction, log_prob = tf.nn.ctc_beam_search_decoder(tf.transpose(self.phonemes,[1,0,2]), self.seq_len, top_paths=topk_paths, merge_repeated=False)
+
+        self.loss_summary = tf.summary.scalar("loss", self.loss)
+        self.merged = tf.summary.merge_all()
+
+    def _nn_conv_bn_layer(self, inputs, scope, shape, strides):
+        with tf.variable_scope(scope):
+            W_conv = tf.get_variable("W", shape=shape, initializer=tf.contrib.layers.xavier_initializer())
+            h_conv = tf.nn.conv2d(inputs, W_conv, strides=[1, strides[0], strides[1], 1], padding='SAME', name="conv2d")
+            b = tf.get_variable("bias" , shape=[shape[3]], initializer=tf.contrib.layers.xavier_initializer())
+            h_bn = tf.layers.batch_normalization(h_conv+b, training = self.isTrain)
+            h_relu = tf.nn.relu6(h_bn, name="relu6")
+            return h_relu
+
+    def _biRNN_bn_layer(self, input, scope, hidden_units, cell = "LayerNormedGRU"):
+        with tf.variable_scope(scope):
+            if cell == 'GRU':
+                fw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LSTM':
+                fw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'vanila':
+                fw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LayerNormedGRU':
+                with tf.variable_scope('fw_cell'):
+                    fw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+                with tf.variable_scope('bw_cell'):
+                    bw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+            else:
+                raise ValueError("Invalid cell type: "+str(cell))
+
+            (output_fw, output_bw), _ = tf.nn.bidirectional_dynamic_rnn(fw_cell, bw_cell, input, dtype=tf.float32, scope="bi_dynamic_rnn")
+            # output_fw_bn = tf.layers.batch_normalization(output_fw, training = self.isTrain, name = 'output_fw_bn')
+            # output_bw_bn = tf.layers.batch_normalization(output_bw, training = self.isTrain, name = 'output_bw_bn')
+            # bilstm_outputs_concat_1 = tf.concat([output_fw_bn, output_bw_bn], 2)
+            bilstm_outputs_concat_1 = tf.concat([output_fw, output_bw], 2)
+            return bilstm_outputs_concat_1
+
+    def train(self, sess, learning_rate, xs, ys):
+        _, loss, summary = sess.run([self.train_op, self.loss, self.merged], feed_dict = {self.isTrain: True, self.learning_rate: learning_rate, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss, summary
+
+    def get_loss(self, sess, xs, ys):
+        loss = sess.run(self.loss, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss
+
+    def predict(self, sess, xs):
+        prediction = sess.run(self.prediction, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs})
+        return prediction
diff --git a/model903.py b/model903.py
new file mode 100644
index 0000000..435975a
--- /dev/null
+++ b/model903.py
@@ -0,0 +1,89 @@
+import tensorflow as tf
+import numpy as np
+from layerNormedGRU import layerNormedGRU
+
+class model:
+
+    def __init__(self, num_class, topk_paths = 10):
+        self.xs = tf.placeholder(tf.float32, [None, 1000, 161])
+        self.ys = tf.sparse_placeholder(tf.int32)
+        self.learning_rate = tf.placeholder(tf.float32)
+        self.seq_len = tf.placeholder(tf.int32, [None])
+        self.isTrain = tf.placeholder(tf.bool, name='phase')
+
+        xs_input = tf.expand_dims(self.xs, 3)
+
+        conv1 = self._nn_conv_bn_layer(xs_input, 'conv_1', [11, 41, 1, 32], [3, 2])
+        conv2 = self._nn_conv_bn_layer(conv1, 'conv_2', [11, 21, 32, 64], [1, 2])
+        conv_out = tf.reshape(conv2, [-1, 334, 41*64])
+        biRNN1 = self._biRNN_bn_layer(conv_out, 'biRNN_1', 1024)
+        biRNN2 = self._biRNN_bn_layer(biRNN1, 'biRNN_2', 1024)
+        biRNN3 = self._biRNN_bn_layer(biRNN2, 'biRNN_3', 1024)
+        biRNN4 = self._biRNN_bn_layer(biRNN3, 'biRNN_4', 1024)
+        biRNN5 = self._biRNN_bn_layer(biRNN4, 'biRNN_5', 1024)
+
+        self.phonemes = tf.layers.dense(biRNN5, num_class)
+
+        # Notes: tf.nn.ctc_loss performs the softmax operation for you, so
+        # inputs should be e.g. linear projections of outputs by an LSTM.
+        self.loss = tf.reduce_mean(tf.nn.ctc_loss(labels=self.ys, inputs=self.phonemes, sequence_length=self.seq_len,
+                                                  ignore_longer_outputs_than_inputs=True, time_major=False))
+
+        optimizer = tf.train.AdamOptimizer(self.learning_rate, beta1=0.7, beta2=0.9)
+        update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
+        with tf.control_dependencies(update_ops):
+            gvs = optimizer.compute_gradients(self.loss)
+            capped_gvs = [(tf.clip_by_value(grad, -400., 400.), var) for grad, var in gvs if grad is not None]
+            self.train_op = optimizer.apply_gradients(capped_gvs)
+
+        self.prediction, log_prob = tf.nn.ctc_beam_search_decoder(tf.transpose(self.phonemes,[1,0,2]), self.seq_len, top_paths=topk_paths, merge_repeated=False)
+
+        self.loss_summary = tf.summary.scalar("loss", self.loss)
+        self.merged = tf.summary.merge_all()
+
+    def _nn_conv_bn_layer(self, inputs, scope, shape, strides):
+        with tf.variable_scope(scope):
+            W_conv = tf.get_variable("W", shape=shape, initializer=tf.contrib.layers.xavier_initializer())
+            h_conv = tf.nn.conv2d(inputs, W_conv, strides=[1, strides[0], strides[1], 1], padding='SAME', name="conv2d")
+            b = tf.get_variable("bias" , shape=[shape[3]], initializer=tf.contrib.layers.xavier_initializer())
+            h_bn = tf.layers.batch_normalization(h_conv+b, training = self.isTrain)
+            h_relu = tf.nn.relu6(h_bn, name="relu6")
+            return h_relu
+
+    def _biRNN_bn_layer(self, input, scope, hidden_units, cell = "LayerNormedGRU"):
+        with tf.variable_scope(scope):
+            if cell == 'GRU':
+                fw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.GRUCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LSTM':
+                fw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'vanila':
+                fw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'fw_cell')
+                bw_cell = tf.nn.rnn_cell.BasicRNNCell(hidden_units, activation=tf.nn.relu, name = 'bw_cell')
+            elif cell == 'LayerNormedGRU':
+                with tf.variable_scope('fw_cell'):
+                    fw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+                with tf.variable_scope('bw_cell'):
+                    bw_cell = layerNormedGRU(hidden_units, activation=tf.nn.relu)
+            else:
+                raise ValueError("Invalid cell type: "+str(cell))
+
+            (output_fw, output_bw), _ = tf.nn.bidirectional_dynamic_rnn(fw_cell, bw_cell, input, dtype=tf.float32, scope="bi_dynamic_rnn")
+            # output_fw_bn = tf.layers.batch_normalization(output_fw, training = self.isTrain, name = 'output_fw_bn')
+            # output_bw_bn = tf.layers.batch_normalization(output_bw, training = self.isTrain, name = 'output_bw_bn')
+            # bilstm_outputs_concat_1 = tf.concat([output_fw_bn, output_bw_bn], 2)
+            bilstm_outputs_concat_1 = tf.concat([output_fw, output_bw], 2)
+            return bilstm_outputs_concat_1
+
+    def train(self, sess, learning_rate, xs, ys):
+        _, loss, summary = sess.run([self.train_op, self.loss, self.merged], feed_dict = {self.isTrain: True, self.learning_rate: learning_rate, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss, summary
+
+    def get_loss(self, sess, xs, ys):
+        loss = sess.run(self.loss, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs, self.ys: ys})
+        return loss
+
+    def predict(self, sess, xs):
+        prediction = sess.run(self.prediction, feed_dict = {self.isTrain: False, self.seq_len: np.ones(xs.shape[0])*334, self.xs: xs})
+        return prediction
diff --git a/subtitle_demo.ipynb b/subtitle_demo.ipynb
new file mode 100644
index 0000000..592f07e
--- /dev/null
+++ b/subtitle_demo.ipynb
@@ -0,0 +1,4363 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import time\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\", message=\"numpy.dtype size changed\")\n",
+    "warnings.filterwarnings(\"ignore\", message=\"numpy.ufunc size changed\")\n",
+    "with warnings.catch_warnings():\n",
+    "    warnings.simplefilter(\"ignore\")\n",
+    "    import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from urllib.request import urlopen\n",
+    "\n",
+    "from lib.tools_batch import *\n",
+    "from lib.tools_math import *\n",
+    "from lib.tools_sparse import *\n",
+    "from lib.tools_audio import *\n",
+    "from lib.contrib.audio_featurizer import AudioFeaturizer\n",
+    "from lib.contrib.audio import AudioSegment\n",
+    "from model903 import *\n",
+    "model_name = \"v903\"\n",
+    "\n",
+    "def timeStamp2Num(timeStamp, rate):\n",
+    "    \"\"\"\n",
+    "    timeStamp str: 00:00:01,879\n",
+    "    rate int: the sampling rate\n",
+    "    return int\n",
+    "    \"\"\"\n",
+    "    secs, millisec = timeStamp.split(\",\")\n",
+    "    hour, minute, sec = secs.split(\":\")\n",
+    "    millisec = float(millisec)*0.001\n",
+    "    sec = float(hour)*3600+float(minute)*60+float(sec)\n",
+    "    num = int(rate*(sec+millisec))\n",
+    "    return num\n",
+    "\n",
+    "pyParser = pinyinParser(\"lib/pinyinDictNoTone.pickle\")\n",
+    "model = model(409)\n",
+    "af = AudioFeaturizer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sess = tf.Session()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Restoring parameters from models/v903/v903_0.ckpt\n"
+     ]
+    }
+   ],
+   "source": [
+    "saver = tf.train.Saver()\n",
+    "saver.restore(sess, \"models/\"+model_name+\"/\"+model_name+\"_0.ckpt\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tamenxiangmusuodingdezhuyaokehuqunjiushiyouhaiwaizhiyexuqiudehuaren\n",
+      "他们项目锁定的主要客户群就是有海外置业需求的华人\n"
+     ]
+    }
+   ],
+   "source": [
+    "rate, data = read_wav(\"data/test.wav\")\n",
+    "data = mergeChannels(data)\n",
+    "data = zero_padding_1d(data, 160240)\n",
+    "a_seg = AudioSegment(data, rate)\n",
+    "xs = np.transpose(np.array([af.featurize(a_seg)]), [0,2,1])\n",
+    "\n",
+    "pred = model.predict(sess, xs)[0]\n",
+    "pred_dense = sparseTuples2dense(pred)\n",
+    "detected_line = []\n",
+    "for stuff in pred_dense[0]:\n",
+    "    if stuff!=-1:\n",
+    "        detected_line.append(stuff)\n",
+    "pinyin = pyParser.decodeIndices(detected_line, useUnderline = False)\n",
+    "print(pinyin)\n",
+    "response = urlopen(\"https://www.google.com/inputtools/request?ime=pinyin&ie=utf-8&oe=utf-8&app=translate&num=10&text=\"+pinyin)\n",
+    "html = response.read()\n",
+    "result = (html.decode('utf8')).split(\",\")[2][2:-1]\n",
+    "print(result)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0/2707\n",
+      "1/2707\n",
+      "Audio time = 3.0 sec.\n",
+      "2/2707\n",
+      "3/2707\n",
+      "4/2707\n",
+      "5/2707\n",
+      "6/2707\n",
+      "Audio time = 1.93 sec.\n",
+      "Recognition time = 8.552099704742432 sec.\n",
+      "大家好\n",
+      "大家好\n",
+      "7/2707\n",
+      "8/2707\n",
+      "9/2707\n",
+      "10/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 11.099024057388306 sec.\n",
+      "或持来自华中科学大学的章洛伊\n",
+      "我是来自华中科技大学的张珞颖\n",
+      "11/2707\n",
+      "12/2707\n",
+      "13/2707\n",
+      "14/2707\n",
+      "Audio time = 2.7 sec.\n",
+      "Recognition time = 11.181823015213013 sec.\n",
+      "我今天给伊达家呆了一个官\n",
+      "我今天给大家带来一个\n",
+      "15/2707\n",
+      "16/2707\n",
+      "17/2707\n",
+      "18/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 11.755331039428711 sec.\n",
+      "在一个关于我们为什么要睡觉的演讲\n",
+      "关于我们为什么要睡觉的演讲\n",
+      "19/2707\n",
+      "20/2707\n",
+      "21/2707\n",
+      "22/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 9.625288963317871 sec.\n",
+      "我们已身中带来有三分之一的时间\n",
+      "我们一生中大概有三分之一的时间\n",
+      "23/2707\n",
+      "24/2707\n",
+      "25/2707\n",
+      "26/2707\n",
+      "Audio time = 2.7 sec.\n",
+      "Recognition time = 9.863281965255737 sec.\n",
+      "是在睡眠中度过的\n",
+      "是在睡眠中度过的\n",
+      "27/2707\n",
+      "28/2707\n",
+      "29/2707\n",
+      "30/2707\n",
+      "31/2707\n",
+      "Audio time = 2.87 sec.\n",
+      "Recognition time = 8.321897983551025 sec.\n",
+      "你从出生到现在\n",
+      "那么你从出生到现在\n",
+      "32/2707\n",
+      "33/2707\n",
+      "34/2707\n",
+      "35/2707\n",
+      "Audio time = 2.83 sec.\n",
+      "Recognition time = 8.540001153945923 sec.\n",
+      "先大概睡了能有十年的叫了\n",
+      "大概睡了能有10年的觉了\n",
+      "36/2707\n",
+      "37/2707\n",
+      "38/2707\n",
+      "39/2707\n",
+      "Audio time = 5.9 sec.\n",
+      "Recognition time = 8.908971071243286 sec.\n",
+      "如果从一个跟宏大的岩画的背景上面来看的话\n",
+      "如果从一个更宏大的演化的背景上面来看的话\n",
+      "40/2707\n",
+      "41/2707\n",
+      "42/2707\n",
+      "43/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 9.589301109313965 sec.\n",
+      "其实睡眠这个现象\n",
+      "其实睡眠这个现象\n",
+      "44/2707\n",
+      "45/2707\n",
+      "46/2707\n",
+      "47/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 9.76643681526184 sec.\n",
+      "在地球上出现了已经有数亿年了\n",
+      "在地球上出现了已经有数亿年了\n",
+      "48/2707\n",
+      "49/2707\n",
+      "50/2707\n",
+      "51/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 10.031269073486328 sec.\n",
+      "就是地球上的动物均水了基因链的角恶\n",
+      "就是地球上的动物已经睡了几亿年的觉了\n",
+      "52/2707\n",
+      "53/2707\n",
+      "54/2707\n",
+      "55/2707\n",
+      "Audio time = 5.18 sec.\n",
+      "Recognition time = 9.635947942733765 sec.\n",
+      "从一个最简单的蠕虫类的东贤重\n",
+      "从一个最简单的蠕虫类的动物 线虫\n",
+      "56/2707\n",
+      "57/2707\n",
+      "58/2707\n",
+      "59/2707\n",
+      "Audio time = 3.0 sec.\n",
+      "Recognition time = 9.9219069480896 sec.\n",
+      "老根复杂的生物\n",
+      "到更复杂的生物\n",
+      "60/2707\n",
+      "61/2707\n",
+      "62/2707\n",
+      "63/2707\n",
+      "Audio time = 2.35 sec.\n",
+      "Recognition time = 10.111473798751831 sec.\n",
+      "比如说昆虫\n",
+      "比如说昆虫\n",
+      "64/2707\n",
+      "65/2707\n",
+      "66/2707\n",
+      "67/2707\n",
+      "Audio time = 2.9 sec.\n",
+      "Recognition time = 9.876278162002563 sec.\n",
+      "然后还有一些鱼类\n",
+      "然后还有一些鱼类\n",
+      "68/2707\n",
+      "69/2707\n",
+      "70/2707\n",
+      "71/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 9.803333759307861 sec.\n",
+      "还有一些哺乳动物\n",
+      "还有一些哺乳动物\n",
+      "72/2707\n",
+      "73/2707\n",
+      "74/2707\n",
+      "75/2707\n",
+      "Audio time = 5.3 sec.\n",
+      "Recognition time = 9.907963037490845 sec.\n",
+      "就又跟我们人类跟接近的这种类似睡眠的状态\n",
+      "就有跟我们人类更接近的这种类似睡眠的状态\n",
+      "76/2707\n",
+      "77/2707\n",
+      "78/2707\n",
+      "79/2707\n",
+      "Audio time = 3.08 sec.\n",
+      "Recognition time = 9.725907802581787 sec.\n",
+      "所以试了很多年的交\n",
+      "所以睡了很多年的觉\n",
+      "80/2707\n",
+      "81/2707\n",
+      "82/2707\n",
+      "83/2707\n",
+      "Audio time = 3.92 sec.\n",
+      "Recognition time = 9.657794713973999 sec.\n",
+      "其实我们并不是特别清楚\n",
+      "其实我们并不是特别清楚\n",
+      "84/2707\n",
+      "85/2707\n",
+      "86/2707\n",
+      "87/2707\n",
+      "Audio time = 3.1 sec.\n",
+      "Recognition time = 9.42478609085083 sec.\n",
+      "我们到底是怎么睡觉或者说\n",
+      "我们到底是怎么睡觉的\n",
+      "88/2707\n",
+      "89/2707\n",
+      "90/2707\n",
+      "91/2707\n",
+      "Audio time = 2.53 sec.\n",
+      "Recognition time = 8.29967713356018 sec.\n",
+      "睡眠是怎么发生的\n",
+      "或者说睡眠是怎么发生的\n",
+      "92/2707\n",
+      "93/2707\n",
+      "94/2707\n",
+      "95/2707\n",
+      "Audio time = 4.42 sec.\n",
+      "Recognition time = 10.434919118881226 sec.\n",
+      "要研究这个问题的话\n",
+      "要研究这个问题的话\n",
+      "96/2707\n",
+      "97/2707\n",
+      "98/2707\n",
+      "99/2707\n",
+      "Audio time = 4.67 sec.\n",
+      "Recognition time = 11.414813995361328 sec.\n",
+      "我们首先要搞清楚到底什么是睡眠\n",
+      "我们首先要搞清楚到底什么是睡眠\n",
+      "100/2707\n",
+      "101/2707\n",
+      "102/2707\n",
+      "103/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 10.734432935714722 sec.\n",
+      "我们睡眠从第一章来说\n",
+      "睡眠从定义上来说\n",
+      "104/2707\n",
+      "105/2707\n",
+      "106/2707\n",
+      "107/2707\n",
+      "Audio time = 6.05 sec.\n",
+      "Recognition time = 10.924272060394287 sec.\n",
+      "它是一种行为上禁止而且觉醒阈值身高的状态\n",
+      "它是一种行为上静止而且觉醒阈值升高的状态\n",
+      "108/2707\n",
+      "109/2707\n",
+      "110/2707\n",
+      "111/2707\n",
+      "Audio time = 3.18 sec.\n",
+      "Recognition time = 11.025686979293823 sec.\n",
+      "这个觉醒阈值是什么意思呢\n",
+      "那这个觉醒阈值是什么意思呢\n",
+      "112/2707\n",
+      "113/2707\n",
+      "114/2707\n",
+      "115/2707\n",
+      "Audio time = 4.77 sec.\n",
+      "Recognition time = 10.317650079727173 sec.\n",
+      "就是说当动物或者我们人进入到睡眠的状态以后\n",
+      "就是说当动物或者我们人进入到睡眠的状态以后\n",
+      "116/2707\n",
+      "117/2707\n",
+      "118/2707\n",
+      "119/2707\n",
+      "Audio time = 5.55 sec.\n",
+      "Recognition time = 9.628606081008911 sec.\n",
+      "需要更强的刺激才能让我们或者让动物做出反应\n",
+      "需要更强的刺激才能让我们或者让动物作出反应\n",
+      "120/2707\n",
+      "121/2707\n",
+      "122/2707\n",
+      "123/2707\n",
+      "Audio time = 4.1 sec.\n",
+      "Recognition time = 9.798579216003418 sec.\n",
+      "这个是一个周边邻的老电影的学段\n",
+      "这个是一个卓别林的老电影的选段\n",
+      "124/2707\n",
+      "125/2707\n",
+      "126/2707\n",
+      "127/2707\n",
+      "Audio time = 3.32 sec.\n",
+      "Recognition time = 10.634912014007568 sec.\n",
+      "那从这个里面我们可以看到\n",
+      "从这个里面我们可以看到\n",
+      "128/2707\n",
+      "129/2707\n",
+      "130/2707\n",
+      "131/2707\n",
+      "Audio time = 3.05 sec.\n",
+      "Recognition time = 10.852342128753662 sec.\n",
+      "一只狗在他醒酒的时候\n",
+      "一只狗在它醒着的时候\n",
+      "132/2707\n",
+      "133/2707\n",
+      "134/2707\n",
+      "135/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 10.997154235839844 sec.\n",
+      "我们只要接近他他就会有反映\n",
+      "我们只要接近它 它就会有反应\n",
+      "136/2707\n",
+      "137/2707\n",
+      "138/2707\n",
+      "139/2707\n",
+      "Audio time = 2.78 sec.\n",
+      "Recognition time = 10.418154001235962 sec.\n",
+      "但是当这个狗睡觉了\n",
+      "但是当这个狗睡着了\n",
+      "140/2707\n",
+      "141/2707\n",
+      "142/2707\n",
+      "143/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 11.395659923553467 sec.\n",
+      "我们临他到耳朵根他的一把\n",
+      "我们拎它的耳朵 拎它的尾巴\n",
+      "144/2707\n",
+      "145/2707\n",
+      "146/2707\n",
+      "147/2707\n",
+      "Audio time = 1.88 sec.\n",
+      "Recognition time = 9.629563093185425 sec.\n",
+      "他都没有反应\n",
+      "它都没有反应\n",
+      "148/2707\n",
+      "149/2707\n",
+      "150/2707\n",
+      "151/2707\n",
+      "Audio time = 3.15 sec.\n",
+      "Recognition time = 10.90805196762085 sec.\n",
+      "这就是决心与纸的身高\n",
+      "这就是觉醒阈值的升高\n",
+      "152/2707\n",
+      "153/2707\n",
+      "154/2707\n",
+      "155/2707\n",
+      "Audio time = 3.18 sec.\n",
+      "Recognition time = 11.129576921463013 sec.\n",
+      "如果要研究睡眠的话\n",
+      "如果要研究睡眠的话\n",
+      "156/2707\n",
+      "157/2707\n",
+      "158/2707\n",
+      "159/2707\n",
+      "Audio time = 3.42 sec.\n",
+      "Recognition time = 11.296210050582886 sec.\n",
+      "我是边还有两个基本的特就\n",
+      "睡眠还有两个基本的特征\n",
+      "160/2707\n",
+      "161/2707\n",
+      "162/2707\n",
+      "163/2707\n",
+      "Audio time = 3.98 sec.\n",
+      "Recognition time = 10.546897888183594 sec.\n",
+      "一个就是睡眠再会积累\n",
+      "一个就是睡眠债会积累\n",
+      "164/2707\n",
+      "165/2707\n",
+      "166/2707\n",
+      "167/2707\n",
+      "Audio time = 2.37 sec.\n",
+      "Recognition time = 9.545593023300171 sec.\n",
+      "去了较北部\n",
+      "缺了觉得补\n",
+      "168/2707\n",
+      "169/2707\n",
+      "170/2707\n",
+      "171/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 10.384339809417725 sec.\n",
+      "这个再生非常有一个专有的名称\n",
+      "这个在生物学上有一个专有的名称\n",
+      "172/2707\n",
+      "173/2707\n",
+      "174/2707\n",
+      "175/2707\n",
+      "Audio time = 3.47 sec.\n",
+      "Recognition time = 9.970831871032715 sec.\n",
+      "我们把它叫做睡眠的稳态平衡\n",
+      "我们把它叫做睡眠的稳态平衡\n",
+      "176/2707\n",
+      "177/2707\n",
+      "178/2707\n",
+      "179/2707\n",
+      "Audio time = 2.45 sec.\n",
+      "Recognition time = 9.712466955184937 sec.\n",
+      "然后另外一点就是水\n",
+      "另外一点就是\n",
+      "180/2707\n",
+      "181/2707\n",
+      "182/2707\n",
+      "183/2707\n",
+      "Audio time = 4.12 sec.\n",
+      "Recognition time = 10.458830118179321 sec.\n",
+      "就是睡眠一般发生在一天中相对固定的时段\n",
+      "睡眠一般发生在一天中相对固定的时段\n",
+      "184/2707\n",
+      "185/2707\n",
+      "186/2707\n",
+      "187/2707\n",
+      "Audio time = 3.98 sec.\n",
+      "Recognition time = 9.82994270324707 sec.\n",
+      "对宇宙性动物就是白天活动的动物\n",
+      "对于昼行动物 就是白天活动的动物\n",
+      "188/2707\n",
+      "189/2707\n",
+      "190/2707\n",
+      "191/2707\n",
+      "Audio time = 2.02 sec.\n",
+      "Recognition time = 10.913809061050415 sec.\n",
+      "比如说我们人类\n",
+      "比如说我们人类\n",
+      "192/2707\n",
+      "193/2707\n",
+      "194/2707\n",
+      "195/2707\n",
+      "Audio time = 3.02 sec.\n",
+      "Recognition time = 11.307654857635498 sec.\n",
+      "睡眠通常发生在夜间\n",
+      "睡眠通常发生在夜间\n",
+      "196/2707\n",
+      "197/2707\n",
+      "198/2707\n",
+      "199/2707\n",
+      "Audio time = 3.27 sec.\n",
+      "Recognition time = 10.648503065109253 sec.\n",
+      "而对于夜行动物比如说小数\n",
+      "而对于夜行动物 比如说小鼠\n",
+      "200/2707\n",
+      "201/2707\n",
+      "202/2707\n",
+      "203/2707\n",
+      "Audio time = 2.88 sec.\n",
+      "Recognition time = 9.821253776550293 sec.\n",
+      "那睡眠通常法人在白天\n",
+      "睡眠通常发生在白天\n",
+      "204/2707\n",
+      "205/2707\n",
+      "206/2707\n",
+      "207/2707\n",
+      "Audio time = 4.77 sec.\n",
+      "Recognition time = 11.648120880126953 sec.\n",
+      "能么要验证睡眠的话我们首先要能够测量睡眠\n",
+      "要研究睡眠的话我们首先要能够测量睡眠\n",
+      "208/2707\n",
+      "209/2707\n",
+      "210/2707\n",
+      "211/2707\n",
+      "Audio time = 3.53 sec.\n",
+      "Recognition time = 10.890952825546265 sec.\n",
+      "最标准的测量睡眠的方法\n",
+      "最标准的测量睡眠的方法\n",
+      "212/2707\n",
+      "213/2707\n",
+      "214/2707\n",
+      "215/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 10.134207010269165 sec.\n",
+      "就是通过监测腦電波\n",
+      "就是通过检测脑电波\n",
+      "216/2707\n",
+      "217/2707\n",
+      "218/2707\n",
+      "219/2707\n",
+      "Audio time = 4.45 sec.\n",
+      "Recognition time = 10.546654224395752 sec.\n",
+      "老电波是由我们脑内的神经元产生的\n",
+      "脑电波是由我们脑内的神经元产生的\n",
+      "220/2707\n",
+      "221/2707\n",
+      "222/2707\n",
+      "223/2707\n",
+      "Audio time = 5.67 sec.\n",
+      "Recognition time = 10.137505769729614 sec.\n",
+      "然后神经元是我们脑内最重要的一种神经细胞\n",
+      "神经元是我们脑内最重要的一种神经细胞\n",
+      "224/2707\n",
+      "225/2707\n",
+      "226/2707\n",
+      "227/2707\n",
+      "Audio time = 5.3 sec.\n",
+      "Recognition time = 10.029753684997559 sec.\n",
+      "他他在齿形它的功能的时候\n",
+      "它在执行它的功能的时候\n",
+      "228/2707\n",
+      "229/2707\n",
+      "230/2707\n",
+      "231/2707\n",
+      "232/2707\n",
+      "Audio time = 5.05 sec.\n",
+      "Recognition time = 10.653613805770874 sec.\n",
+      "这种方便体现在整个脑的层面竟是脑电波\n",
+      "这种放电体现在整个脑的层面就是脑电波\n",
+      "233/2707\n",
+      "234/2707\n",
+      "235/2707\n",
+      "236/2707\n",
+      "Audio time = 3.22 sec.\n",
+      "Recognition time = 9.727614879608154 sec.\n",
+      "在我们醒着和睡着的时候\n",
+      "在我们醒着和睡着的时候\n",
+      "237/2707\n",
+      "238/2707\n",
+      "239/2707\n",
+      "240/2707\n",
+      "Audio time = 4.25 sec.\n",
+      "Recognition time = 11.570410966873169 sec.\n",
+      "脑电波发放的平率和模式是不一样的\n",
+      "脑电波发放的频率和模式是不一样的\n",
+      "241/2707\n",
+      "242/2707\n",
+      "243/2707\n",
+      "244/2707\n",
+      "Audio time = 3.07 sec.\n",
+      "Recognition time = 11.969449996948242 sec.\n",
+      "所以通过这种方式\n",
+      "所以通过这种方式\n",
+      "245/2707\n",
+      "246/2707\n",
+      "247/2707\n",
+      "248/2707\n",
+      "Audio time = 3.35 sec.\n",
+      "Recognition time = 10.143391370773315 sec.\n",
+      "就可以判断这个人或者这个动物\n",
+      "就可以判断这个人或者这个动物\n",
+      "249/2707\n",
+      "250/2707\n",
+      "251/2707\n",
+      "252/2707\n",
+      "Audio time = 4.03 sec.\n",
+      "Recognition time = 11.102733850479126 sec.\n",
+      "动物是处于清醒的状态还是睡眠的状态\n",
+      "是处于清醒的状态还是睡眠的状态\n",
+      "253/2707\n",
+      "254/2707\n",
+      "255/2707\n",
+      "256/2707\n",
+      "Audio time = 4.78 sec.\n",
+      "Recognition time = 11.26534104347229 sec.\n",
+      "们这边又变得就有一些典型的脑电波的代表土\n",
+      "右边就有一些典型的脑电波的代表图\n",
+      "257/2707\n",
+      "258/2707\n",
+      "259/2707\n",
+      "260/2707\n",
+      "Audio time = 4.0 sec.\n",
+      "Recognition time = 11.73793888092041 sec.\n",
+      "对对于色地使我们清醒的时候的闹过\n",
+      "绿色是我们清醒时候的脑波\n",
+      "261/2707\n",
+      "262/2707\n",
+      "263/2707\n",
+      "264/2707\n",
+      "Audio time = 4.4 sec.\n",
+      "Recognition time = 11.047256231307983 sec.\n",
+      "根据睡眠状态的时候我们的眼球是否转动\n",
+      "根据睡眠状态的时候我们的眼球是否转动\n",
+      "265/2707\n",
+      "266/2707\n",
+      "267/2707\n",
+      "268/2707\n",
+      "Audio time = 5.1 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 10.043828964233398 sec.\n",
+      "睡眠又会被分为动眼睡眠和不动眼睡眠\n",
+      "睡眠又会被分为动眼睡眠和不动眼睡眠\n",
+      "269/2707\n",
+      "270/2707\n",
+      "271/2707\n",
+      "272/2707\n",
+      "Audio time = 3.13 sec.\n",
+      "Recognition time = 9.584776163101196 sec.\n",
+      "动睡眠不说我们人类可有的\n",
+      "动眼睡眠不光是我们人类特有的\n",
+      "273/2707\n",
+      "274/2707\n",
+      "275/2707\n",
+      "276/2707\n",
+      "Audio time = 3.05 sec.\n",
+      "Recognition time = 10.095137119293213 sec.\n",
+      "我们通常我所说的几个做梦\n",
+      "我们通常所说的做梦\n",
+      "277/2707\n",
+      "278/2707\n",
+      "279/2707\n",
+      "280/2707\n",
+      "281/2707\n",
+      "Audio time = 4.1 sec.\n",
+      "Recognition time = 9.666446208953857 sec.\n",
+      "大家可能觉得做工很高阶的中线向\n",
+      "大家可能觉得做梦是很高级的一种现象\n",
+      "282/2707\n",
+      "283/2707\n",
+      "284/2707\n",
+      "285/2707\n",
+      "Audio time = 3.43 sec.\n",
+      "Recognition time = 9.769724130630493 sec.\n",
+      "但是在骑士东野的水里面这个阶段\n",
+      "但是其实动眼睡眠这个阶段\n",
+      "286/2707\n",
+      "287/2707\n",
+      "288/2707\n",
+      "289/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 10.027660131454468 sec.\n",
+      "在一些爬行类动物在一些鱼类究竟\n",
+      "在一些爬行类动物 在一些鱼类\n",
+      "290/2707\n",
+      "291/2707\n",
+      "292/2707\n",
+      "293/2707\n",
+      "Audio time = 2.18 sec.\n",
+      "Recognition time = 11.577821254730225 sec.\n",
+      "就已经拍时出现了\n",
+      "就已经开始出现了\n",
+      "294/2707\n",
+      "295/2707\n",
+      "296/2707\n",
+      "297/2707\n",
+      "Audio time = 2.95 sec.\n",
+      "Recognition time = 11.365415811538696 sec.\n",
+      "所以可能不止我们人会做梦\n",
+      "所以可能不只我们人会做梦\n",
+      "298/2707\n",
+      "299/2707\n",
+      "300/2707\n",
+      "301/2707\n",
+      "Audio time = 2.43 sec.\n",
+      "Recognition time = 10.037224054336548 sec.\n",
+      "包括小刷\n",
+      "包括小鼠\n",
+      "302/2707\n",
+      "303/2707\n",
+      "304/2707\n",
+      "305/2707\n",
+      "Audio time = 5.47 sec.\n",
+      "Recognition time = 10.851239204406738 sec.\n",
+      "然后写鱼鸟可能都可以做梦\n",
+      "然后一些鱼 鸟可能都可以做梦\n",
+      "306/2707\n",
+      "307/2707\n",
+      "308/2707\n",
+      "309/2707\n",
+      "Audio time = 4.53 sec.\n",
+      "Recognition time = 11.36710786819458 sec.\n",
+      "我动员睡眠的根据台的脑电波发放模式的不同\n",
+      "不动眼睡眠根据它的脑电波发放模式的不同\n",
+      "310/2707\n",
+      "311/2707\n",
+      "312/2707\n",
+      "313/2707\n",
+      "Audio time = 4.32 sec.\n",
+      "Recognition time = 10.881148099899292 sec.\n",
+      "不会被分为一根儿和恩善散的阶段\n",
+      "会被分为N1 N2和N3三个阶段\n",
+      "314/2707\n",
+      "315/2707\n",
+      "316/2707\n",
+      "317/2707\n",
+      "Audio time = 4.62 sec.\n",
+      "Recognition time = 10.397065877914429 sec.\n",
+      "这个红色就是跟完阶段的脑电波\n",
+      "这个红色的就是N2阶段的脑电波\n",
+      "318/2707\n",
+      "319/2707\n",
+      "320/2707\n",
+      "321/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.470474004745483 sec.\n",
+      "一阶段因为跟清醒的时候比较像\n",
+      "N1阶段因为跟清醒的时候比较像\n",
+      "322/2707\n",
+      "323/2707\n",
+      "324/2707\n",
+      "325/2707\n",
+      "Audio time = 2.3499375 sec.\n",
+      "Recognition time = 10.86468243598938 sec.\n",
+      "这里没有展示出来\n",
+      "这里没有展示出来\n",
+      "326/2707\n",
+      "327/2707\n",
+      "328/2707\n",
+      "329/2707\n",
+      "Audio time = 4.6699375 sec.\n",
+      "Recognition time = 10.574501991271973 sec.\n",
+      "然后下面这个蓝色的呢是本三结对\n",
+      "然后下面这个蓝色的是N3阶段\n",
+      "330/2707\n",
+      "331/2707\n",
+      "332/2707\n",
+      "333/2707\n",
+      "334/2707\n",
+      "Audio time = 7.1 sec.\n",
+      "Recognition time = 11.44644021987915 sec.\n",
+      "这个是一个健康的成年人一晚上的睡眠分布图\n",
+      "这个是一个健康的成年人一晚上的睡眠分布图\n",
+      "335/2707\n",
+      "336/2707\n",
+      "337/2707\n",
+      "338/2707\n",
+      "Audio time = 4.38 sec.\n",
+      "Recognition time = 9.783345222473145 sec.\n",
+      "我可以看到首先会来到这个另一阶段\n",
+      "我们可以看到首先会来到这个N1阶段\n",
+      "339/2707\n",
+      "340/2707\n",
+      "341/2707\n",
+      "342/2707\n",
+      "Audio time = 5.48 sec.\n",
+      "Recognition time = 9.822526931762695 sec.\n",
+      "然后一阶段大概很多只有两三分钟就结束了\n",
+      "N1阶段大概很短 只有两三分钟就结束了\n",
+      "343/2707\n",
+      "344/2707\n",
+      "345/2707\n",
+      "346/2707\n",
+      "Audio time = 5.18 sec.\n",
+      "Recognition time = 9.965109825134277 sec.\n",
+      "然后之后会进入到不动员睡眠的恶骂二阶段\n",
+      "之后会进入到不动眼睡眠的N2阶段\n",
+      "347/2707\n",
+      "348/2707\n",
+      "349/2707\n",
+      "350/2707\n",
+      "Audio time = 5.07 sec.\n",
+      "Recognition time = 10.915495157241821 sec.\n",
+      "让恩而切断一般会持续二十到三十分钟\n",
+      "N2阶段一般会持续20到30分钟\n",
+      "351/2707\n",
+      "352/2707\n",
+      "353/2707\n",
+      "354/2707\n",
+      "Audio time = 3.72 sec.\n",
+      "Recognition time = 10.996959924697876 sec.\n",
+      "然后就进又到了深度深绵恩三阶段\n",
+      "然后就进入到了深度睡眠N3阶段\n",
+      "355/2707\n",
+      "356/2707\n",
+      "357/2707\n",
+      "358/2707\n",
+      "Audio time = 5.37 sec.\n",
+      "Recognition time = 11.775229930877686 sec.\n",
+      "等三节大概也会有摆个小时到四十分钟\n",
+      "N3阶段大概会有半个小时到40分钟\n",
+      "359/2707\n",
+      "360/2707\n",
+      "361/2707\n",
+      "362/2707\n",
+      "Audio time = 3.08 sec.\n",
+      "Recognition time = 10.342374801635742 sec.\n",
+      "然后之后又进入到了华尔街段\n",
+      "之后又进入到N2阶段\n",
+      "363/2707\n",
+      "364/2707\n",
+      "365/2707\n",
+      "366/2707\n",
+      "Audio time = 3.97 sec.\n",
+      "Recognition time = 9.932070016860962 sec.\n",
+      "然后完了以后就会经入道这个图上红色标记的\n",
+      "完了以后就会进入到图上红色标记的\n",
+      "367/2707\n",
+      "368/2707\n",
+      "369/2707\n",
+      "370/2707\n",
+      "Audio time = 2.48 sec.\n",
+      "Recognition time = 9.448712348937988 sec.\n",
+      "动眼睡眠阶段\n",
+      "动眼睡眠阶段\n",
+      "371/2707\n",
+      "372/2707\n",
+      "373/2707\n",
+      "374/2707\n",
+      "Audio time = 3.22 sec.\n",
+      "Recognition time = 9.702091932296753 sec.\n",
+      "这个时候就开始做梦了\n",
+      "这个时候就开始做梦了\n",
+      "375/2707\n",
+      "376/2707\n",
+      "377/2707\n",
+      "378/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 9.725405931472778 sec.\n",
+      "我们夜间第一次说梦网时间很短\n",
+      "我们夜间第一次做梦时间很短\n",
+      "379/2707\n",
+      "380/2707\n",
+      "381/2707\n",
+      "382/2707\n",
+      "Audio time = 2.63 sec.\n",
+      "Recognition time = 9.727473020553589 sec.\n",
+      "他该球季分钟就解说了\n",
+      "大概几分钟就结束了\n",
+      "383/2707\n",
+      "384/2707\n",
+      "385/2707\n",
+      "386/2707\n",
+      "Audio time = 5.02 sec.\n",
+      "Recognition time = 9.932792901992798 sec.\n",
+      "然后完了以后就会进入到不懂夜睡眠的恶化而本三\n",
+      "完了以后又会进入到不动眼睡眠的N2 N3\n",
+      "387/2707\n",
+      "388/2707\n",
+      "389/2707\n",
+      "390/2707\n",
+      "Audio time = 2.45 sec.\n",
+      "Recognition time = 9.547476053237915 sec.\n",
+      "然后问三赛道德观\n",
+      "然后N3再到N2\n",
+      "391/2707\n",
+      "392/2707\n",
+      "393/2707\n",
+      "394/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 9.805496215820312 sec.\n",
+      "然后再到这个动眼睡眠的琢磨了阶段\n",
+      "然后再到动眼睡眠的做梦的阶段\n",
+      "395/2707\n",
+      "396/2707\n",
+      "397/2707\n",
+      "398/2707\n",
+      "Audio time = 3.07 sec.\n",
+      "Recognition time = 9.727619886398315 sec.\n",
+      "中间可能他会玩醒来几次\n",
+      "中间可能还会偶尔醒来几次\n",
+      "399/2707\n",
+      "400/2707\n",
+      "401/2707\n",
+      "402/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 9.62583303451538 sec.\n",
+      "所以我们以诚月的睡眠\n",
+      "所以我们一整夜的睡眠\n",
+      "403/2707\n",
+      "404/2707\n",
+      "405/2707\n",
+      "406/2707\n",
+      "Audio time = 3.95 sec.\n",
+      "Recognition time = 10.813950777053833 sec.\n",
+      "大概就是在东衍义补洞沿水面舰\n",
+      "大概就是在动眼与不动眼睡眠间\n",
+      "407/2707\n",
+      "408/2707\n",
+      "409/2707\n",
+      "410/2707\n",
+      "Audio time = 2.8 sec.\n",
+      "Recognition time = 9.664967775344849 sec.\n",
+      "交替我付进行的\n",
+      "交替往复进行的\n",
+      "411/2707\n",
+      "412/2707\n",
+      "413/2707\n",
+      "414/2707\n",
+      "Audio time = 4.1 sec.\n",
+      "Recognition time = 9.705291032791138 sec.\n",
+      "但是总过再说我们从初上可以看出来一个趋势\n",
+      "但是总的来说我们从图上可以看出来一个趋势\n",
+      "415/2707\n",
+      "416/2707\n",
+      "417/2707\n",
+      "418/2707\n",
+      "Audio time = 4.75 sec.\n",
+      "Recognition time = 9.852061986923218 sec.\n",
+      "就是不动员睡眠恩三阶段的这个深冬睡眠\n",
+      "就是不动眼睡眠N3阶段的深度睡眠\n",
+      "419/2707\n",
+      "420/2707\n",
+      "421/2707\n",
+      "422/2707\n",
+      "Audio time = 4.33 sec.\n",
+      "Recognition time = 9.65317416191101 sec.\n",
+      "主要发生在前半夜就是铅似的消失\n",
+      "主要发生在前半夜 就是前4个小时\n",
+      "423/2707\n",
+      "424/2707\n",
+      "425/2707\n",
+      "426/2707\n",
+      "Audio time = 3.97 sec.\n",
+      "Recognition time = 9.98378324508667 sec.\n",
+      "然后动眼睡眠做梦主要发生在后半叶\n",
+      "动眼睡眠 做梦 主要发生在后半夜\n",
+      "427/2707\n",
+      "428/2707\n",
+      "429/2707\n",
+      "430/2707\n",
+      "431/2707\n",
+      "Audio time = 3.77 sec.\n",
+      "Recognition time = 9.622798204421997 sec.\n",
+      "因为我觉得这个厂子还挺适合搭客岁的\n",
+      "因为我觉得这个场子还挺适合打瞌睡的\n",
+      "432/2707\n",
+      "433/2707\n",
+      "434/2707\n",
+      "435/2707\n",
+      "Audio time = 5.0 sec.\n",
+      "Recognition time = 9.85256028175354 sec.\n",
+      "如果说我在演讲的时候你们睡着了就很正常\n",
+      "如果说我在演讲的时候你们睡着了这很正常\n",
+      "436/2707\n",
+      "437/2707\n",
+      "438/2707\n",
+      "439/2707\n",
+      "Audio time = 3.83 sec.\n",
+      "Recognition time = 11.778626203536987 sec.\n",
+      "但是我在演讲的时候我睡着了\n",
+      "但如果我在演讲的时候我睡着了\n",
+      "440/2707\n",
+      "441/2707\n",
+      "442/2707\n",
+      "443/2707\n",
+      "Audio time = 2.87 sec.\n",
+      "Recognition time = 10.750944137573242 sec.\n",
+      "这个可能就是使水镇了\n",
+      "这个可能就是嗜睡症了\n",
+      "444/2707\n",
+      "445/2707\n",
+      "446/2707\n",
+      "447/2707\n",
+      "Audio time = 3.68 sec.\n",
+      "Recognition time = 9.830672025680542 sec.\n",
+      "是水生患者可以在任何的时候\n",
+      "嗜睡症患者可以在任何时候\n",
+      "448/2707\n",
+      "449/2707\n",
+      "450/2707\n",
+      "451/2707\n",
+      "Audio time = 3.87 sec.\n",
+      "Recognition time = 9.829492807388306 sec.\n",
+      "比如说说话的时候站着走路的时候\n",
+      "比如说说话的时候 站着 走路的时候\n",
+      "452/2707\n",
+      "453/2707\n",
+      "454/2707\n",
+      "455/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 9.539852857589722 sec.\n",
+      "都有可能随时睡着\n",
+      "都有可能随时睡着\n",
+      "456/2707\n",
+      "457/2707\n",
+      "458/2707\n",
+      "459/2707\n",
+      "Audio time = 4.25 sec.\n",
+      "Recognition time = 10.017771005630493 sec.\n",
+      "比如说这个左边这个视频就位小朋友他正在大嚼\n",
+      "比如说左边这个视频里这位小朋友他正在大叫\n",
+      "460/2707\n",
+      "461/2707\n",
+      "462/2707\n",
+      "463/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 9.604837894439697 sec.\n",
+      "然后突然就睡着了\n",
+      "然后突然就睡着了\n",
+      "464/2707\n",
+      "465/2707\n",
+      "466/2707\n",
+      "467/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 9.748177766799927 sec.\n",
+      "然不光是人有时睡着\n",
+      "不光是人有嗜睡症\n",
+      "468/2707\n",
+      "469/2707\n",
+      "470/2707\n",
+      "471/2707\n",
+      "Audio time = 1.85 sec.\n",
+      "Recognition time = 9.727482080459595 sec.\n",
+      "这种动物也有\n",
+      "动物也有\n",
+      "472/2707\n",
+      "473/2707\n",
+      "474/2707\n",
+      "475/2707\n",
+      "Audio time = 3.9 sec.\n",
+      "Recognition time = 10.34311318397522 sec.\n",
+      "比如说右边的视频里了举止够\n",
+      "比如说右边的视频里的这只狗\n",
+      "476/2707\n",
+      "477/2707\n",
+      "478/2707\n",
+      "479/2707\n",
+      "Audio time = 3.23 sec.\n",
+      "Recognition time = 9.853617906570435 sec.\n",
+      "他跑着袍子然后就高了睡觉了\n",
+      "它跑着跑着然后就倒了 睡着了\n",
+      "480/2707\n",
+      "481/2707\n",
+      "482/2707\n",
+      "483/2707\n",
+      "Audio time = 1.97 sec.\n",
+      "Recognition time = 10.190370082855225 sec.\n",
+      "还有个特写\n",
+      "还有个特写\n",
+      "484/2707\n",
+      "485/2707\n",
+      "486/2707\n",
+      "487/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 10.981247186660767 sec.\n",
+      "不要解释是随证\n",
+      "要解释嗜睡症\n",
+      "488/2707\n",
+      "489/2707\n",
+      "490/2707\n",
+      "491/2707\n",
+      "Audio time = 4.35 sec.\n",
+      "Recognition time = 10.111642122268677 sec.\n",
+      "我们就要先解释一下水面到底是怎么产生的\n",
+      "我们就要先解释一下睡眠到底是怎么产生的\n",
+      "492/2707\n",
+      "493/2707\n",
+      "494/2707\n",
+      "495/2707\n",
+      "Audio time = 4.62 sec.\n",
+      "Recognition time = 10.934529781341553 sec.\n",
+      "从环路的从一个宏观的环的层面来说\n",
+      "从一个宏观的环路的层面来说\n",
+      "496/2707\n",
+      "497/2707\n",
+      "498/2707\n",
+      "499/2707\n",
+      "Audio time = 2.48 sec.\n",
+      "Recognition time = 9.775462865829468 sec.\n",
+      "睡眠主要是因为\n",
+      "睡眠主要是因为\n",
+      "500/2707\n",
+      "501/2707\n",
+      "502/2707\n",
+      "503/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 9.83092212677002 sec.\n",
+      "因为我们脑内有一些促进睡眠的脑区\n",
+      "我们脑内有一些促进睡眠的脑区\n",
+      "504/2707\n",
+      "505/2707\n",
+      "506/2707\n",
+      "507/2707\n",
+      "Audio time = 1.9 sec.\n",
+      "Recognition time = 9.625238180160522 sec.\n",
+      "他活跃了\n",
+      "它活跃了\n",
+      "508/2707\n",
+      "509/2707\n",
+      "510/2707\n",
+      "511/2707\n",
+      "Audio time = 4.2 sec.\n",
+      "Recognition time = 9.93152403831482 sec.\n",
+      "然后抑制了一些促进清醒的脑区的活动\n",
+      "然后抑制了一些促进清醒的脑区的活动\n",
+      "512/2707\n",
+      "513/2707\n",
+      "514/2707\n",
+      "515/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 9.728116035461426 sec.\n",
+      "这样子睡眠就发生了\n",
+      "这样子睡眠就发生了\n",
+      "516/2707\n",
+      "517/2707\n",
+      "518/2707\n",
+      "519/2707\n",
+      "Audio time = 4.85 sec.\n",
+      "Recognition time = 9.830097913742065 sec.\n",
+      "然后在我们脑内有一个叫做下丘脑的部位\n",
+      "然后在我们脑内有一个叫做下丘脑的部位\n",
+      "520/2707\n",
+      "521/2707\n",
+      "522/2707\n",
+      "523/2707\n",
+      "Audio time = 3.41 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 9.830487966537476 sec.\n",
+      "它分泌右边这个图里的这种叫做\n",
+      "它分泌右边这个图里的这种\n",
+      "524/2707\n",
+      "525/2707\n",
+      "526/2707\n",
+      "527/2707\n",
+      "Audio time = 2.64 sec.\n",
+      "Recognition time = 9.749634981155396 sec.\n",
+      "焦作市欲诉的起诉\n",
+      "叫做食欲素的激素\n",
+      "528/2707\n",
+      "529/2707\n",
+      "530/2707\n",
+      "531/2707\n",
+      "Audio time = 2.9 sec.\n",
+      "Recognition time = 9.705573797225952 sec.\n",
+      "这个时日苏轼一个堕胎\n",
+      "这个食欲素是一个多肽\n",
+      "532/2707\n",
+      "533/2707\n",
+      "534/2707\n",
+      "535/2707\n",
+      "Audio time = 2.98 sec.\n",
+      "Recognition time = 9.728498935699463 sec.\n",
+      "然后他又出轻型的作用\n",
+      "然后它有促清醒的作用\n",
+      "536/2707\n",
+      "537/2707\n",
+      "538/2707\n",
+      "539/2707\n",
+      "Audio time = 5.42 sec.\n",
+      "Recognition time = 9.726438999176025 sec.\n",
+      "所以在我们脑内分别是语素的脑区\n",
+      "所以在我们脑内分泌这个食欲素的脑区\n",
+      "540/2707\n",
+      "541/2707\n",
+      "542/2707\n",
+      "543/2707\n",
+      "Audio time = 2.28 sec.\n",
+      "Recognition time = 9.878099918365479 sec.\n",
+      "如果出现了问题\n",
+      "如果出现了问题\n",
+      "544/2707\n",
+      "545/2707\n",
+      "546/2707\n",
+      "547/2707\n",
+      "Audio time = 5.27 sec.\n",
+      "Recognition time = 9.774406909942627 sec.\n",
+      "让这个是匀速不能正常分离了就回的嗜睡症\n",
+      "让这个食欲素不能正常分泌了就会得嗜睡症\n",
+      "548/2707\n",
+      "549/2707\n",
+      "550/2707\n",
+      "551/2707\n",
+      "Audio time = 5.25 sec.\n",
+      "Recognition time = 9.71791696548462 sec.\n",
+      "如果反过来内邪从水面的脑区出现问题的话\n",
+      "如果反过来那些促睡眠的脑区出现问题的话\n",
+      "552/2707\n",
+      "553/2707\n",
+      "554/2707\n",
+      "555/2707\n",
+      "Audio time = 2.37 sec.\n",
+      "Recognition time = 9.643173933029175 sec.\n",
+      "那就可能会导致失眠\n",
+      "那就可能会导致失眠\n",
+      "556/2707\n",
+      "557/2707\n",
+      "558/2707\n",
+      "559/2707\n",
+      "Audio time = 4.0 sec.\n",
+      "Recognition time = 9.830233812332153 sec.\n",
+      "这个是从一个宏观的关东的层面来\n",
+      "这个是从一个宏观的环路的层面\n",
+      "560/2707\n",
+      "561/2707\n",
+      "562/2707\n",
+      "563/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 10.698323965072632 sec.\n",
+      "曾来解释睡眠是怎么产生的\n",
+      "来解释睡眠是怎么产生的\n",
+      "564/2707\n",
+      "565/2707\n",
+      "566/2707\n",
+      "567/2707\n",
+      "Audio time = 4.65 sec.\n",
+      "Recognition time = 9.882713079452515 sec.\n",
+      "下面我再介绍一下从更微观的分子的层面\n",
+      "下面我再介绍一下从更微观的分子层面\n",
+      "568/2707\n",
+      "569/2707\n",
+      "570/2707\n",
+      "571/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 9.650267124176025 sec.\n",
+      "睡眠是怎么产生的\n",
+      "睡眠是怎么产生的\n",
+      "572/2707\n",
+      "573/2707\n",
+      "574/2707\n",
+      "575/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 9.773362874984741 sec.\n",
+      "这就要回到我前面说的一个概念了\n",
+      "这就要回到我前面说的一个概念\n",
+      "576/2707\n",
+      "577/2707\n",
+      "578/2707\n",
+      "579/2707\n",
+      "Audio time = 3.33 sec.\n",
+      "Recognition time = 10.030200958251953 sec.\n",
+      "就是睡眠的稳态平衡\n",
+      "就是睡眠的稳态平衡\n",
+      "580/2707\n",
+      "581/2707\n",
+      "582/2707\n",
+      "583/2707\n",
+      "Audio time = 3.75 sec.\n",
+      "Recognition time = 10.664466142654419 sec.\n",
+      "这个稳态平衡其实一直都在进行\n",
+      "这个稳态平衡其实一直都在进行\n",
+      "584/2707\n",
+      "585/2707\n",
+      "586/2707\n",
+      "587/2707\n",
+      "Audio time = 2.96 sec.\n",
+      "Recognition time = 10.670705795288086 sec.\n",
+      "在我们现在醒着的时候\n",
+      "在我们现在醒着的时候\n",
+      "588/2707\n",
+      "589/2707\n",
+      "590/2707\n",
+      "591/2707\n",
+      "Audio time = 2.46 sec.\n",
+      "Recognition time = 9.720854043960571 sec.\n",
+      "是时刻个都在进行\n",
+      "时时刻刻都在进行\n",
+      "592/2707\n",
+      "593/2707\n",
+      "594/2707\n",
+      "595/2707\n",
+      "Audio time = 3.82 sec.\n",
+      "Recognition time = 9.638154983520508 sec.\n",
+      "然后它的作用就是他会积累睡眠债\n",
+      "它的作用就是它会积累睡眠债\n",
+      "596/2707\n",
+      "597/2707\n",
+      "598/2707\n",
+      "599/2707\n",
+      "Audio time = 2.23 sec.\n",
+      "Recognition time = 9.72170901298523 sec.\n",
+      "或者说睡眠压力\n",
+      "或者说睡眠压力\n",
+      "600/2707\n",
+      "601/2707\n",
+      "602/2707\n",
+      "603/2707\n",
+      "Audio time = 3.55 sec.\n",
+      "Recognition time = 9.701176881790161 sec.\n",
+      "大家现在听到这的已经是与领悟力的心\n",
+      "大家现在听到这里已经是云里雾里了\n",
+      "604/2707\n",
+      "605/2707\n",
+      "606/2707\n",
+      "607/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 9.857541799545288 sec.\n",
+      "新田就像这位专家请说扔花\n",
+      "心里就想 这位专家 请说人话\n",
+      "608/2707\n",
+      "609/2707\n",
+      "610/2707\n",
+      "611/2707\n",
+      "Audio time = 7.17 sec.\n",
+      "Recognition time = 9.861650228500366 sec.\n",
+      "通俗地说着稳态平衡会持续的积累困意\n",
+      "通俗地说这个稳态平衡它会持续地积累困意\n",
+      "612/2707\n",
+      "613/2707\n",
+      "614/2707\n",
+      "615/2707\n",
+      "Audio time = 3.45 sec.\n",
+      "Recognition time = 9.621397018432617 sec.\n",
+      "就是我们行得越久我们会觉得越困\n",
+      "就是我们醒得越久我们会觉得越困\n",
+      "616/2707\n",
+      "617/2707\n",
+      "618/2707\n",
+      "619/2707\n",
+      "Audio time = 3.19 sec.\n",
+      "Recognition time = 9.552765130996704 sec.\n",
+      "这种困意其实就是\n",
+      "这种困意其实就是\n",
+      "620/2707\n",
+      "621/2707\n",
+      "622/2707\n",
+      "623/2707\n",
+      "Audio time = 4.26 sec.\n",
+      "Recognition time = 9.753791093826294 sec.\n",
+      "稳态平衡机制金磊睡眠压力的体现\n",
+      "稳态平衡机制积累睡眠压力的体现\n",
+      "624/2707\n",
+      "625/2707\n",
+      "626/2707\n",
+      "627/2707\n",
+      "Audio time = 3.38 sec.\n",
+      "Recognition time = 9.642898321151733 sec.\n",
+      "那么这个坤到底是什么呢\n",
+      "这个困到底是什么呢\n",
+      "628/2707\n",
+      "629/2707\n",
+      "630/2707\n",
+      "631/2707\n",
+      "Audio time = 5.27 sec.\n",
+      "Recognition time = 10.137492895126343 sec.\n",
+      "在我们的脑内有一种叫做腺甘的化学物质\n",
+      "在我们的脑内有一种叫做腺苷的化学物质\n",
+      "632/2707\n",
+      "633/2707\n",
+      "634/2707\n",
+      "635/2707\n",
+      "Audio time = 2.52 sec.\n",
+      "Recognition time = 9.99905800819397 sec.\n",
+      "在我们醒着的时候\n",
+      "在我们醒着的时候\n",
+      "636/2707\n",
+      "637/2707\n",
+      "638/2707\n",
+      "639/2707\n",
+      "Audio time = 5.1 sec.\n",
+      "Recognition time = 10.277492046356201 sec.\n",
+      "这项安徽在脑内移植及泪不停的积累\n",
+      "这个腺苷会在脑内一直积累 不停地积累\n",
+      "640/2707\n",
+      "641/2707\n",
+      "642/2707\n",
+      "643/2707\n",
+      "Audio time = 3.8 sec.\n",
+      "Recognition time = 9.665159940719604 sec.\n",
+      "然后他会有一个促进睡眠的作用\n",
+      "然后它会有一个促进睡眠的作用\n",
+      "644/2707\n",
+      "645/2707\n",
+      "646/2707\n",
+      "647/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 9.89172887802124 sec.\n",
+      "如果我们这样想\n",
+      "如果我们这样想\n",
+      "648/2707\n",
+      "649/2707\n",
+      "650/2707\n",
+      "651/2707\n",
+      "Audio time = 4.4 sec.\n",
+      "Recognition time = 9.931124925613403 sec.\n",
+      "如果有一种方法可以对抗着相爱的作用\n",
+      "如果有一种方法可以对抗这个腺苷的作用\n",
+      "652/2707\n",
+      "653/2707\n",
+      "654/2707\n",
+      "655/2707\n",
+      "Audio time = 5.22 sec.\n",
+      "Recognition time = 9.63114595413208 sec.\n",
+      "但是不是我们就我可以不不觉得困难\n",
+      "那是不是我们就可以不觉得困了\n",
+      "656/2707\n",
+      "657/2707\n",
+      "658/2707\n",
+      "659/2707\n",
+      "660/2707\n",
+      "Audio time = 2.92 sec.\n",
+      "Recognition time = 9.92594313621521 sec.\n",
+      "后那确实是有这样的方法的\n",
+      "确实是有这样的方法的\n",
+      "661/2707\n",
+      "662/2707\n",
+      "663/2707\n",
+      "664/2707\n",
+      "Audio time = 6.63 sec.\n",
+      "Recognition time = 9.932551145553589 sec.\n",
+      "最常用的一种可以对抗腺苷的物质就是咖啡应\n",
+      "最常用的一种可以对抗腺苷的物质就是咖啡因\n",
+      "665/2707\n",
+      "666/2707\n",
+      "667/2707\n",
+      "668/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 9.727835893630981 sec.\n",
+      "它存在于图上这些我们\n",
+      "它存在于图上这些\n",
+      "669/2707\n",
+      "670/2707\n",
+      "671/2707\n",
+      "672/2707\n",
+      "Audio time = 4.68 sec.\n",
+      "Recognition time = 9.776414394378662 sec.\n",
+      "我们每天可能都在应用的应聘当中\n",
+      "我们每天可能都在饮用的饮品当中\n",
+      "673/2707\n",
+      "674/2707\n",
+      "675/2707\n",
+      "676/2707\n",
+      "Audio time = 7.0999375 sec.\n",
+      "Recognition time = 9.667120933532715 sec.\n",
+      "包括像咖啡红牛各种茶还有可能等等\n",
+      "包括像咖啡 红牛 各种茶 还有可乐等等\n",
+      "677/2707\n",
+      "678/2707\n",
+      "679/2707\n",
+      "680/2707\n",
+      "Audio time = 6.071 sec.\n",
+      "Recognition time = 9.94428014755249 sec.\n",
+      "这个像安踏在我们脑内是可以跟它的受体结合\n",
+      "这个腺苷它在我们脑内是可以跟它的受体结合\n",
+      "681/2707\n",
+      "682/2707\n",
+      "683/2707\n",
+      "684/2707\n",
+      "Audio time = 2.3 sec.\n",
+      "Recognition time = 9.938446998596191 sec.\n",
+      "从而促进睡眠\n",
+      "从而促进睡眠\n",
+      "685/2707\n",
+      "686/2707\n",
+      "687/2707\n",
+      "688/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 10.423325061798096 sec.\n",
+      "那咖啡人作用就是看\n",
+      "咖啡因的作用就是\n",
+      "689/2707\n",
+      "690/2707\n",
+      "691/2707\n",
+      "692/2707\n",
+      "Audio time = 3.15 sec.\n",
+      "Recognition time = 10.562416791915894 sec.\n",
+      "就是咖啡因会跟线杆的受体结合\n",
+      "咖啡因会跟腺苷的受体结合\n",
+      "693/2707\n",
+      "694/2707\n",
+      "695/2707\n",
+      "696/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 10.547760963439941 sec.\n",
+      "让岘港不能跟他自己的手地结合\n",
+      "让腺苷不能跟它自己的受体结合\n",
+      "697/2707\n",
+      "698/2707\n",
+      "699/2707\n",
+      "700/2707\n",
+      "Audio time = 4.25 sec.\n",
+      "Recognition time = 9.930874109268188 sec.\n",
+      "这样就可以一直睡眠促进清晰\n",
+      "这样就可以抑制睡眠 促进清醒\n",
+      "701/2707\n",
+      "702/2707\n",
+      "703/2707\n",
+      "704/2707\n",
+      "Audio time = 4.45 sec.\n",
+      "Recognition time = 9.728864908218384 sec.\n",
+      "相爱是我前面提到的各\n",
+      "腺苷是我前面提到的那个\n",
+      "705/2707\n",
+      "706/2707\n",
+      "707/2707\n",
+      "708/2707\n",
+      "709/2707\n",
+      "Audio time = 2.83 sec.\n",
+      "Recognition time = 9.697293758392334 sec.\n",
+      "但是他不是唯一的媒介\n",
+      "但是它不是唯一的媒介\n",
+      "710/2707\n",
+      "711/2707\n",
+      "712/2707\n",
+      "713/2707\n",
+      "Audio time = 4.82 sec.\n",
+      "Recognition time = 10.371662139892578 sec.\n",
+      "还有其他许多粉丝都参与到了这个调控过程中\n",
+      "还有其他许多分子都参与到了这个调控过程中\n",
+      "714/2707\n",
+      "715/2707\n",
+      "716/2707\n",
+      "717/2707\n",
+      "Audio time = 4.0 sec.\n",
+      "Recognition time = 10.035088777542114 sec.\n",
+      "我们可以把稳态平衡机制肖湘成一个杀戮\n",
+      "我们可以把稳态平衡机制想象成一个沙漏\n",
+      "718/2707\n",
+      "719/2707\n",
+      "720/2707\n",
+      "721/2707\n",
+      "Audio time = 2.77 sec.\n",
+      "Recognition time = 9.7845139503479 sec.\n",
+      "在我们醒着的时候\n",
+      "在我们醒着的时候\n",
+      "722/2707\n",
+      "723/2707\n",
+      "724/2707\n",
+      "725/2707\n",
+      "Audio time = 5.1 sec.\n",
+      "Recognition time = 9.939879894256592 sec.\n",
+      "个我太平衡其实它会一直的积累我们的睡眠压力\n",
+      "这个稳态平衡机制它会一直地积累我们的睡眠压力\n",
+      "726/2707\n",
+      "727/2707\n",
+      "728/2707\n",
+      "729/2707\n",
+      "Audio time = 3.32 sec.\n",
+      "Recognition time = 11.504558086395264 sec.\n",
+      "然后到我们进入到睡眠的时候\n",
+      "然后到我们进入到睡眠的时候\n",
+      "730/2707\n",
+      "731/2707\n",
+      "732/2707\n",
+      "733/2707\n",
+      "734/2707\n",
+      "Audio time = 3.23 sec.\n",
+      "Recognition time = 10.95905089378357 sec.\n",
+      "但这个水边压力释放关闭以后\n",
+      "当这个睡眠压力释放完毕以后\n",
+      "735/2707\n",
+      "736/2707\n",
+      "737/2707\n",
+      "738/2707\n",
+      "Audio time = 1.9 sec.\n",
+      "Recognition time = 9.931496858596802 sec.\n",
+      "睡眠就会结束\n",
+      "睡眠就会结束\n",
+      "739/2707\n",
+      "740/2707\n",
+      "741/2707\n",
+      "742/2707\n",
+      "Audio time = 1.95 sec.\n",
+      "Recognition time = 9.603691101074219 sec.\n",
+      "我们会醒来\n",
+      "我们会醒来\n",
+      "743/2707\n",
+      "744/2707\n",
+      "745/2707\n",
+      "746/2707\n",
+      "Audio time = 3.32 sec.\n",
+      "Recognition time = 9.71631908416748 sec.\n",
+      "我们可以想象如果在醒着的时候\n",
+      "我们可以想象如果在醒着的时候\n",
+      "747/2707\n",
+      "748/2707\n",
+      "749/2707\n",
+      "750/2707\n",
+      "Audio time = 2.7 sec.\n",
+      "Recognition time = 9.863147974014282 sec.\n",
+      "我们挤在越多的睡眠压力\n",
+      "我们积累越多的睡眠压力\n",
+      "751/2707\n",
+      "752/2707\n",
+      "753/2707\n",
+      "754/2707\n",
+      "Audio time = 3.0 sec.\n",
+      "Recognition time = 9.725075960159302 sec.\n",
+      "也就意味着说进入睡眠以后\n",
+      "那就意味着说进入睡眠以后\n",
+      "755/2707\n",
+      "756/2707\n",
+      "757/2707\n",
+      "758/2707\n",
+      "Audio time = 2.42 sec.\n",
+      "Recognition time = 9.627044200897217 sec.\n",
+      "需要更长的时间\n",
+      "需要更长的时间\n",
+      "759/2707\n",
+      "760/2707\n",
+      "761/2707\n",
+      "762/2707\n",
+      "Audio time = 3.22 sec.\n",
+      "Recognition time = 11.06000804901123 sec.\n",
+      "才能把这些水被压力释放干净\n",
+      "才能把这些睡眠压力释放干净\n",
+      "763/2707\n",
+      "764/2707\n",
+      "765/2707\n",
+      "766/2707\n",
+      "Audio time = 2.55 sec.\n",
+      "Recognition time = 9.931901931762695 sec.\n",
+      "那也就意味的是我们可能\n",
+      "那也就意味着说\n",
+      "767/2707\n",
+      "768/2707\n",
+      "769/2707\n",
+      "770/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 9.831027269363403 sec.\n",
+      "我们可能会睡得更就是一个跟神\n",
+      "我们可能会睡得更久 睡得更深\n",
+      "771/2707\n",
+      "772/2707\n",
+      "773/2707\n",
+      "774/2707\n",
+      "Audio time = 3.47 sec.\n",
+      "Recognition time = 10.13632583618164 sec.\n",
+      "我太平衡晶石的左右其实就在这里\n",
+      "稳态平衡机制的作用其实就在这里\n",
+      "775/2707\n",
+      "776/2707\n",
+      "777/2707\n",
+      "778/2707\n",
+      "Audio time = 3.38 sec.\n",
+      "Recognition time = 10.238585948944092 sec.\n",
+      "它是决定我们睡多久和水多深\n",
+      "它是决定我们睡多久和睡多深\n",
+      "779/2707\n",
+      "780/2707\n",
+      "781/2707\n",
+      "782/2707\n",
+      "Audio time = 3.3 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 9.539638996124268 sec.\n",
+      "所以如果你一夜没睡熬夜了\n",
+      "所以如果你一夜没睡 熬夜了\n",
+      "783/2707\n",
+      "784/2707\n",
+      "785/2707\n",
+      "786/2707\n",
+      "Audio time = 3.87 sec.\n",
+      "Recognition time = 9.81445574760437 sec.\n",
+      "离第二天就会睡得比平时要酒喝声\n",
+      "你第二天就会睡得比平时要久和深\n",
+      "787/2707\n",
+      "788/2707\n",
+      "789/2707\n",
+      "790/2707\n",
+      "Audio time = 3.68 sec.\n",
+      "Recognition time = 9.829972982406616 sec.\n",
+      "然后如果说这个工作日睡的比较少\n",
+      "如果说你工作日睡得比较少\n",
+      "791/2707\n",
+      "792/2707\n",
+      "793/2707\n",
+      "794/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 9.848114728927612 sec.\n",
+      "那周末可能就会要不教会\n",
+      "那周末可能就会要补觉\n",
+      "795/2707\n",
+      "796/2707\n",
+      "797/2707\n",
+      "798/2707\n",
+      "Audio time = 3.52 sec.\n",
+      "Recognition time = 10.671857118606567 sec.\n",
+      "回水到特别的就特别的深\n",
+      "会睡得特别地久 特别地深\n",
+      "799/2707\n",
+      "800/2707\n",
+      "801/2707\n",
+      "802/2707\n",
+      "Audio time = 3.15 sec.\n",
+      "Recognition time = 11.05112338066101 sec.\n",
+      "可以所以从这里我们可以看出来\n",
+      "所以从这里我们可以看出来\n",
+      "803/2707\n",
+      "804/2707\n",
+      "805/2707\n",
+      "806/2707\n",
+      "Audio time = 3.93 sec.\n",
+      "Recognition time = 11.739706039428711 sec.\n",
+      "七十个睡眠呀离婚者所睡眠债一个\n",
+      "其实这个睡眠压力或者说睡眠债\n",
+      "807/2707\n",
+      "808/2707\n",
+      "809/2707\n",
+      "810/2707\n",
+      "Audio time = 3.92 sec.\n",
+      "Recognition time = 11.164644002914429 sec.\n",
+      "再以跟我们签的所有其他债一样都是要还的\n",
+      "跟我们欠的所有其他债一样 都是要还的\n",
+      "811/2707\n",
+      "812/2707\n",
+      "813/2707\n",
+      "814/2707\n",
+      "Audio time = 3.43 sec.\n",
+      "Recognition time = 11.262641906738281 sec.\n",
+      "对我前面讲到了水面这两大特征\n",
+      "我前面讲到的睡眠的两大特征\n",
+      "815/2707\n",
+      "816/2707\n",
+      "817/2707\n",
+      "818/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 11.49067497253418 sec.\n",
+      "一个是他收到我太平和机制的调控\n",
+      "一个是它受到稳态平衡机制的调控\n",
+      "819/2707\n",
+      "820/2707\n",
+      "821/2707\n",
+      "822/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 9.9706711769104 sec.\n",
+      "然后另外一点就是她还\n",
+      "另外一点就是\n",
+      "823/2707\n",
+      "824/2707\n",
+      "825/2707\n",
+      "826/2707\n",
+      "Audio time = 3.47 sec.\n",
+      "Recognition time = 10.385109901428223 sec.\n",
+      "他还会发展在一天中相对固定的时段\n",
+      "它还会发生在一天中相对固定的时段\n",
+      "827/2707\n",
+      "828/2707\n",
+      "829/2707\n",
+      "830/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 10.632283210754395 sec.\n",
+      "对于我们人类来说主要是在夜间\n",
+      "对我们人类来说主要是在夜间\n",
+      "831/2707\n",
+      "832/2707\n",
+      "833/2707\n",
+      "834/2707\n",
+      "Audio time = 2.8 sec.\n",
+      "Recognition time = 10.150068044662476 sec.\n",
+      "但是基本说在液晶睡觉\n",
+      "但是即便说在夜间睡觉\n",
+      "835/2707\n",
+      "836/2707\n",
+      "837/2707\n",
+      "838/2707\n",
+      "Audio time = 3.75 sec.\n",
+      "Recognition time = 11.003652095794678 sec.\n",
+      "谁叫我相信在座的大家可能作息时间\n",
+      "我相信在座的大家可能作息时间\n",
+      "839/2707\n",
+      "840/2707\n",
+      "841/2707\n",
+      "842/2707\n",
+      "Audio time = 2.2 sec.\n",
+      "Recognition time = 11.117875099182129 sec.\n",
+      "都还挺不一样的\n",
+      "都还挺不一样的\n",
+      "843/2707\n",
+      "844/2707\n",
+      "845/2707\n",
+      "846/2707\n",
+      "Audio time = 5.9 sec.\n",
+      "Recognition time = 11.228707075119019 sec.\n",
+      "比如说这个在座的可能有这种早睡早起的每天\n",
+      "比如说在座的可能有这种早睡早起的\n",
+      "847/2707\n",
+      "848/2707\n",
+      "849/2707\n",
+      "850/2707\n",
+      "Audio time = 2.85 sec.\n",
+      "Recognition time = 10.889628887176514 sec.\n",
+      "每天教廷我的不是道中\n",
+      "每天叫醒我的不是闹钟\n",
+      "851/2707\n",
+      "852/2707\n",
+      "853/2707\n",
+      "854/2707\n",
+      "855/2707\n",
+      "Audio time = 3.52 sec.\n",
+      "Recognition time = 10.766643047332764 sec.\n",
+      "最终我们叫做白领聊性的坐骑\n",
+      "这种我们叫做百灵鸟型的作息\n",
+      "856/2707\n",
+      "857/2707\n",
+      "858/2707\n",
+      "859/2707\n",
+      "Audio time = 3.17 sec.\n",
+      "Recognition time = 10.757474184036255 sec.\n",
+      "然后也会有晚睡晚起的\n",
+      "然后也会有晚睡晚起的\n",
+      "860/2707\n",
+      "861/2707\n",
+      "862/2707\n",
+      "863/2707\n",
+      "Audio time = 3.55 sec.\n",
+      "Recognition time = 11.207590818405151 sec.\n",
+      "每天最大的越王可能就是睡到十二点的\n",
+      "每天最大的愿望可能就是睡到12点的\n",
+      "864/2707\n",
+      "865/2707\n",
+      "866/2707\n",
+      "867/2707\n",
+      "Audio time = 2.9 sec.\n",
+      "Recognition time = 10.9791841506958 sec.\n",
+      "这就毛佗硬性的做些\n",
+      "这种猫头鹰型的作息\n",
+      "868/2707\n",
+      "869/2707\n",
+      "870/2707\n",
+      "871/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 10.691560983657837 sec.\n",
+      "就是我个人而言\n",
+      "就我个人而言\n",
+      "872/2707\n",
+      "873/2707\n",
+      "874/2707\n",
+      "875/2707\n",
+      "Audio time = 3.75 sec.\n",
+      "Recognition time = 11.438000917434692 sec.\n",
+      "如果我不是我外界因素的干扰\n",
+      "如果我不受外界因素的干扰\n",
+      "876/2707\n",
+      "877/2707\n",
+      "878/2707\n",
+      "879/2707\n",
+      "Audio time = 4.8 sec.\n",
+      "Recognition time = 10.490594148635864 sec.\n",
+      "那我大概是凌晨三点睡到上午十点异性\n",
+      "那我大概是凌晨3点睡 然后上午10点醒\n",
+      "880/2707\n",
+      "881/2707\n",
+      "882/2707\n",
+      "883/2707\n",
+      "Audio time = 3.83 sec.\n",
+      "Recognition time = 8.91028118133545 sec.\n",
+      "所以我也是一个典型的檐帽子型的\n",
+      "所以我也是一个典型的夜猫子型\n",
+      "884/2707\n",
+      "885/2707\n",
+      "886/2707\n",
+      "887/2707\n",
+      "Audio time = 2.46 sec.\n",
+      "Recognition time = 11.33391809463501 sec.\n",
+      "毛陀硬性的做些\n",
+      "猫头鹰型的作息\n",
+      "888/2707\n",
+      "889/2707\n",
+      "890/2707\n",
+      "891/2707\n",
+      "Audio time = 4.68 sec.\n",
+      "Recognition time = 9.400279760360718 sec.\n",
+      "从我们从小到大受的教育可能会觉得\n",
+      "我们从小到大受的教育可能会觉得\n",
+      "892/2707\n",
+      "893/2707\n",
+      "894/2707\n",
+      "895/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 10.655029058456421 sec.\n",
+      "这种不同的作息制度\n",
+      "这种不同的作息制度\n",
+      "896/2707\n",
+      "897/2707\n",
+      "898/2707\n",
+      "899/2707\n",
+      "Audio time = 3.27 sec.\n",
+      "Recognition time = 9.58838677406311 sec.\n",
+      "跟你是情分还是懒惰\n",
+      "跟你是勤奋还是懒惰\n",
+      "900/2707\n",
+      "901/2707\n",
+      "902/2707\n",
+      "903/2707\n",
+      "Audio time = 3.73 sec.\n",
+      "Recognition time = 12.32562804222107 sec.\n",
+      "你们有一个好的生活和学习习惯有关系\n",
+      "你有没有一个好的生活和学习习惯有关系\n",
+      "904/2707\n",
+      "905/2707\n",
+      "906/2707\n",
+      "907/2707\n",
+      "Audio time = 3.62 sec.\n",
+      "Recognition time = 11.26798677444458 sec.\n",
+      "但是其实也不一定吃这样\n",
+      "但是其实也不一定是这样\n",
+      "908/2707\n",
+      "909/2707\n",
+      "910/2707\n",
+      "911/2707\n",
+      "Audio time = 5.72 sec.\n",
+      "Recognition time = 11.97499394416809 sec.\n",
+      "在上个世纪的九十年代\n",
+      "在上个世纪的90年代\n",
+      "912/2707\n",
+      "913/2707\n",
+      "914/2707\n",
+      "915/2707\n",
+      "Audio time = 5.17 sec.\n",
+      "Recognition time = 10.610878944396973 sec.\n",
+      "在美国有个犹他大学的睡眠尊属\n",
+      "在美国有个犹他大学的睡眠诊所\n",
+      "916/2707\n",
+      "917/2707\n",
+      "918/2707\n",
+      "919/2707\n",
+      "Audio time = 3.23 sec.\n",
+      "Recognition time = 12.025944709777832 sec.\n",
+      "然后有一天有一位睡眠医生迎来\n",
+      "有一天有一位睡眠医生\n",
+      "920/2707\n",
+      "921/2707\n",
+      "922/2707\n",
+      "923/2707\n",
+      "Audio time = 4.7 sec.\n",
+      "Recognition time = 11.564014196395874 sec.\n",
+      "艺声引来了一个老太太六十多岁老太太叫做代替\n",
+      "迎来了一个60多岁的老太太 叫做Becky\n",
+      "924/2707\n",
+      "925/2707\n",
+      "926/2707\n",
+      "927/2707\n",
+      "Audio time = 3.81 sec.\n",
+      "Recognition time = 8.943893909454346 sec.\n",
+      "这个白厅就跟着渭水边医生说\n",
+      "这个Becky就跟这位睡眠医生说\n",
+      "928/2707\n",
+      "929/2707\n",
+      "930/2707\n",
+      "931/2707\n",
+      "Audio time = 3.89 sec.\n",
+      "Recognition time = 10.408736944198608 sec.\n",
+      "他说卧床小到大都早睡早起\n",
+      "她说我从小到大都早睡早起\n",
+      "932/2707\n",
+      "933/2707\n",
+      "934/2707\n",
+      "935/2707\n",
+      "Audio time = 2.42 sec.\n",
+      "Recognition time = 8.908719301223755 sec.\n",
+      "然后这个沈湎医生说\n",
+      "然后这个睡眠医生说\n",
+      "936/2707\n",
+      "937/2707\n",
+      "938/2707\n",
+      "939/2707\n",
+      "Audio time = 3.58 sec.\n",
+      "Recognition time = 10.541115283966064 sec.\n",
+      "那不是挺好的吗早非早起身体好\n",
+      "那不是挺好的吗 早睡早起身体好\n",
+      "940/2707\n",
+      "941/2707\n",
+      "942/2707\n",
+      "943/2707\n",
+      "Audio time = 2.52 sec.\n",
+      "Recognition time = 9.929500341415405 sec.\n",
+      "然后老太来说\n",
+      "然后老太太说\n",
+      "944/2707\n",
+      "945/2707\n",
+      "946/2707\n",
+      "947/2707\n",
+      "Audio time = 3.45 sec.\n",
+      "Recognition time = 10.349467992782593 sec.\n",
+      "不是你想象那样早睡也早起\n",
+      "不是你想象那样早睡早起\n",
+      "948/2707\n",
+      "949/2707\n",
+      "950/2707\n",
+      "951/2707\n",
+      "Audio time = 5.12 sec.\n",
+      "Recognition time = 10.21029782295227 sec.\n",
+      "我是每天晚上祁烈我就困了时睡觉了\n",
+      "我是每天晚上7点多就困了 然后需要睡觉了\n",
+      "952/2707\n",
+      "953/2707\n",
+      "954/2707\n",
+      "955/2707\n",
+      "Audio time = 3.52 sec.\n",
+      "Recognition time = 10.267696142196655 sec.\n",
+      "凌晨每天凌晨撕裂多就会醒来\n",
+      "每天凌晨4点多就会醒来\n",
+      "956/2707\n",
+      "957/2707\n",
+      "958/2707\n",
+      "959/2707\n",
+      "Audio time = 2.33 sec.\n",
+      "Recognition time = 9.497772932052612 sec.\n",
+      "在我年轻的时候呢\n",
+      "她说在我年轻的时候\n",
+      "960/2707\n",
+      "961/2707\n",
+      "962/2707\n",
+      "963/2707\n",
+      "Audio time = 3.82 sec.\n",
+      "Recognition time = 10.189707040786743 sec.\n",
+      "他说这个对我的生活造成了不小的困扰\n",
+      "这个也对我的生活造成了不小的困扰\n",
+      "964/2707\n",
+      "965/2707\n",
+      "966/2707\n",
+      "967/2707\n",
+      "968/2707\n",
+      "Audio time = 2.73 sec.\n",
+      "Recognition time = 10.070319175720215 sec.\n",
+      "这我都没有办法才加\n",
+      "我都没有办法参加\n",
+      "969/2707\n",
+      "970/2707\n",
+      "971/2707\n",
+      "972/2707\n",
+      "973/2707\n",
+      "Audio time = 3.9 sec.\n",
+      "Recognition time = 9.709878206253052 sec.\n",
+      "然后他说不仅是他是这样\n",
+      "然后她说不仅是她是这样\n",
+      "974/2707\n",
+      "975/2707\n",
+      "976/2707\n",
+      "977/2707\n",
+      "Audio time = 4.5 sec.\n",
+      "Recognition time = 10.216222047805786 sec.\n",
+      "他的母亲他的外祖父他的兄弟\n",
+      "她的母亲 她的外祖父 她的兄弟\n",
+      "978/2707\n",
+      "979/2707\n",
+      "980/2707\n",
+      "981/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 9.88833498954773 sec.\n",
+      "他的女儿甚至是她的外孙女儿\n",
+      "她的女儿 甚至是她的外孙女\n",
+      "982/2707\n",
+      "983/2707\n",
+      "984/2707\n",
+      "985/2707\n",
+      "Audio time = 2.13 sec.\n",
+      "Recognition time = 9.780324220657349 sec.\n",
+      "都是这个样子\n",
+      "都是这个样子\n",
+      "986/2707\n",
+      "987/2707\n",
+      "988/2707\n",
+      "989/2707\n",
+      "Audio time = 3.35 sec.\n",
+      "Recognition time = 10.5138680934906 sec.\n",
+      "他也为这个事情看过很多医生\n",
+      "她也为这个事情看过很多医生\n",
+      "990/2707\n",
+      "991/2707\n",
+      "992/2707\n",
+      "993/2707\n",
+      "Audio time = 3.73 sec.\n",
+      "Recognition time = 9.933246850967407 sec.\n",
+      "内些一身都跟他说他有精神问题\n",
+      "那些医生都跟她说她有精神问题\n",
+      "994/2707\n",
+      "995/2707\n",
+      "996/2707\n",
+      "997/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 10.4442138671875 sec.\n",
+      "所以他也挺困惑的\n",
+      "所以她也挺困惑的\n",
+      "998/2707\n",
+      "999/2707\n",
+      "1000/2707\n",
+      "1001/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 9.666093111038208 sec.\n",
+      "因为他觉得子宇亲身挺正常\n",
+      "因为她觉得自己精神挺正常的\n",
+      "1002/2707\n",
+      "1003/2707\n",
+      "1004/2707\n",
+      "1005/2707\n",
+      "Audio time = 3.58 sec.\n",
+      "Recognition time = 9.941423654556274 sec.\n",
+      "这个睡眠也生听到了这个事情以后\n",
+      "这个睡眠医生听到了这个事情以后\n",
+      "1006/2707\n",
+      "1007/2707\n",
+      "1008/2707\n",
+      "1009/2707\n",
+      "Audio time = 3.05 sec.\n",
+      "Recognition time = 9.780264139175415 sec.\n",
+      "他想这个家族留这么多成员\n",
+      "他想这个家族有这么多成员\n",
+      "1010/2707\n",
+      "1011/2707\n",
+      "1012/2707\n",
+      "1013/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.034083127975464 sec.\n",
+      "于是他就进行了一个系统的调查\n",
+      "于是他就进行了一个系统的调查\n",
+      "1014/2707\n",
+      "1015/2707\n",
+      "1016/2707\n",
+      "1017/2707\n",
+      "Audio time = 4.08 sec.\n",
+      "Recognition time = 9.687443971633911 sec.\n",
+      "发现这个家族中确实有二十九过程远\n",
+      "发现这个家族中确实有29个成员\n",
+      "1018/2707\n",
+      "1019/2707\n",
+      "1020/2707\n",
+      "1021/2707\n",
+      "Audio time = 3.92 sec.\n",
+      "Recognition time = 9.92458701133728 sec.\n",
+      "都有这种吸毒的早睡早起的现象\n",
+      "都有这种极度的早睡早起的现象\n",
+      "1022/2707\n",
+      "1023/2707\n",
+      "1024/2707\n",
+      "1025/2707\n",
+      "Audio time = 5.33 sec.\n",
+      "Recognition time = 10.65902590751648 sec.\n",
+      "其中他又让张国成员到她的歌睡眠中心的因为\n",
+      "其中他又让6个成员到他的睡眠中心来\n",
+      "1026/2707\n",
+      "1027/2707\n",
+      "1028/2707\n",
+      "1029/2707\n",
+      "Audio time = 2.13 sec.\n",
+      "Recognition time = 11.199529886245728 sec.\n",
+      "这个早非早起呢\n",
+      "因为这个早睡早起\n",
+      "1030/2707\n",
+      "1031/2707\n",
+      "1032/2707\n",
+      "1033/2707\n",
+      "Audio time = 3.48 sec.\n",
+      "Recognition time = 10.41060996055603 sec.\n",
+      "不是你说早而造情酒浓酸的\n",
+      "不是你说早睡早起就能算的\n",
+      "1034/2707\n",
+      "1035/2707\n",
+      "1036/2707\n",
+      "1037/2707\n",
+      "Audio time = 3.88 sec.\n",
+      "Recognition time = 10.478367328643799 sec.\n",
+      "对缺失的用脑电波去测量它的睡眠\n",
+      "得确实地用脑电波去测量他的睡眠\n",
+      "1038/2707\n",
+      "1039/2707\n",
+      "1040/2707\n",
+      "1041/2707\n",
+      "Audio time = 2.75 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 8.69693899154663 sec.\n",
+      "开始不是真的早睡早起了\n",
+      "看是不是真的早睡早起了\n",
+      "1042/2707\n",
+      "1043/2707\n",
+      "1044/2707\n",
+      "1045/2707\n",
+      "Audio time = 3.78 sec.\n",
+      "Recognition time = 10.330029964447021 sec.\n",
+      "所以究竟写了用脑电波的对睡眠的测量\n",
+      "所以就进行了用脑电波对睡眠的测量\n",
+      "1046/2707\n",
+      "1047/2707\n",
+      "1048/2707\n",
+      "1049/2707\n",
+      "Audio time = 5.17 sec.\n",
+      "Recognition time = 9.376667737960815 sec.\n",
+      "然后发现这些人他们的睡眠确实如白婷诉说\n",
+      "然后发现这些人他们的睡眠确实如Becky所说\n",
+      "1050/2707\n",
+      "1051/2707\n",
+      "1052/2707\n",
+      "1053/2707\n",
+      "Audio time = 5.05 sec.\n",
+      "Recognition time = 10.506406307220459 sec.\n",
+      "然后这个是比正常的人要造了带盖三个半到四个小时\n",
+      "这个是比正常的人要早大概3个半到4个小时\n",
+      "1054/2707\n",
+      "1055/2707\n",
+      "1056/2707\n",
+      "1057/2707\n",
+      "Audio time = 4.35 sec.\n",
+      "Recognition time = 9.216369152069092 sec.\n",
+      "因为这个现象是这个家族都有\n",
+      "因为这个现象是整个家族都有\n",
+      "1058/2707\n",
+      "1059/2707\n",
+      "1060/2707\n",
+      "1061/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 11.876338958740234 sec.\n",
+      "所以你就是说它是一个可以溢出的现象\n",
+      "所以就是说它是一个可以遗传的现象\n",
+      "1062/2707\n",
+      "1063/2707\n",
+      "1064/2707\n",
+      "1065/2707\n",
+      "Audio time = 4.98 sec.\n",
+      "Recognition time = 10.549348831176758 sec.\n",
+      "这位睡眠一生的就决定进一步的去调查这个事情\n",
+      "这位睡眠医生就决定进一步地去调查这个事情\n",
+      "1066/2707\n",
+      "1067/2707\n",
+      "1068/2707\n",
+      "1069/2707\n",
+      "Audio time = 2.92 sec.\n",
+      "Recognition time = 10.03463888168335 sec.\n",
+      "他和一位遗传学家\n",
+      "他和一位遗传学家\n",
+      "1070/2707\n",
+      "1071/2707\n",
+      "1072/2707\n",
+      "1073/2707\n",
+      "Audio time = 3.93 sec.\n",
+      "Recognition time = 9.010717868804932 sec.\n",
+      "也就是我在美国博士后的导师合作\n",
+      "也就是我在美国博士后的导师合作\n",
+      "1074/2707\n",
+      "1075/2707\n",
+      "1076/2707\n",
+      "1077/2707\n",
+      "Audio time = 2.53 sec.\n",
+      "Recognition time = 8.68841004371643 sec.\n",
+      "然后他们就发现了\n",
+      "他们就发现了\n",
+      "1078/2707\n",
+      "1079/2707\n",
+      "1080/2707\n",
+      "1081/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 9.936977863311768 sec.\n",
+      "们这些特别早睡早起的人\n",
+      "这些特别早睡早起的人\n",
+      "1082/2707\n",
+      "1083/2707\n",
+      "1084/2707\n",
+      "1085/2707\n",
+      "Audio time = 3.65 sec.\n",
+      "Recognition time = 8.949090242385864 sec.\n",
+      "其实是带了一个罕见的基因变异\n",
+      "其实是带了一个罕见的基因变异\n",
+      "1086/2707\n",
+      "1087/2707\n",
+      "1088/2707\n",
+      "1089/2707\n",
+      "Audio time = 4.27 sec.\n",
+      "Recognition time = 9.697094917297363 sec.\n",
+      "这个变异发生在一个叫做裴瑞驰的基因里面\n",
+      "这个变异发生在一个叫做PERIOD2的基因里面\n",
+      "1090/2707\n",
+      "1091/2707\n",
+      "1092/2707\n",
+      "1093/2707\n",
+      "Audio time = 2.92 sec.\n",
+      "Recognition time = 10.638010025024414 sec.\n",
+      "然后这个编译器时就导致了\n",
+      "这个变异其实就导致了\n",
+      "1094/2707\n",
+      "1095/2707\n",
+      "1096/2707\n",
+      "1097/2707\n",
+      "Audio time = 3.78 sec.\n",
+      "Recognition time = 10.272983074188232 sec.\n",
+      "胚乳球的点黑须那上有\n",
+      "PERIOD2的的DNA序列上\n",
+      "1098/2707\n",
+      "1099/2707\n",
+      "1100/2707\n",
+      "1101/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 10.458916902542114 sec.\n",
+      "有一个阶级的改变\n",
+      "有一个碱基对的改变\n",
+      "1102/2707\n",
+      "1103/2707\n",
+      "1104/2707\n",
+      "1105/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 10.171255588531494 sec.\n",
+      "后一个碱基的改变了导致他所编码的基因\n",
+      "然后一个碱基对的改变导致它所编码的基因\n",
+      "1106/2707\n",
+      "1107/2707\n",
+      "1108/2707\n",
+      "1109/2707\n",
+      "Audio time = 4.33 sec.\n",
+      "Recognition time = 10.784722328186035 sec.\n",
+      "渴而除蛋白有一个案子酸的改变\n",
+      "PERIOD2蛋白有一个氨基酸的改变\n",
+      "1110/2707\n",
+      "1111/2707\n",
+      "1112/2707\n",
+      "1113/2707\n",
+      "Audio time = 2.48 sec.\n",
+      "Recognition time = 10.316540956497192 sec.\n",
+      "这么的一个改变\n",
+      "这么一个改变\n",
+      "1114/2707\n",
+      "1115/2707\n",
+      "1116/2707\n",
+      "1117/2707\n",
+      "Audio time = 3.92 sec.\n",
+      "Recognition time = 10.117632150650024 sec.\n",
+      "因为科尔秋瑾是一个生物中的精\n",
+      "因为PERIOD2基因是一个生物钟的基因\n",
+      "1118/2707\n",
+      "1119/2707\n",
+      "1120/2707\n",
+      "1121/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 10.107079029083252 sec.\n",
+      "所以这么一个改变就影响了这些人的生物钟\n",
+      "所以这么一个改变就影响了这些人的生物钟\n",
+      "1122/2707\n",
+      "1123/2707\n",
+      "1124/2707\n",
+      "1125/2707\n",
+      "Audio time = 4.72 sec.\n",
+      "Recognition time = 10.416341066360474 sec.\n",
+      "生物钟我们可大家听说过都听说过名称\n",
+      "生物钟大家可能都听说过这个名称\n",
+      "1126/2707\n",
+      "1127/2707\n",
+      "1128/2707\n",
+      "1129/2707\n",
+      "1130/2707\n",
+      "Audio time = 4.2 sec.\n",
+      "Recognition time = 10.445109128952026 sec.\n",
+      "他其实是我们体内的一种计时机制\n",
+      "它其实是我们体内的一种计时机制\n",
+      "1131/2707\n",
+      "1132/2707\n",
+      "1133/2707\n",
+      "1134/2707\n",
+      "Audio time = 4.65 sec.\n",
+      "Recognition time = 10.649009227752686 sec.\n",
+      "然后它会使我们的各种行为和生理过程\n",
+      "它会使我们的各种行为和生理过程\n",
+      "1135/2707\n",
+      "1136/2707\n",
+      "1137/2707\n",
+      "1138/2707\n",
+      "Audio time = 3.38 sec.\n",
+      "Recognition time = 10.23893690109253 sec.\n",
+      "表现出一种啊是四小时的戒律\n",
+      "表现出一种24小时的节律\n",
+      "1139/2707\n",
+      "1140/2707\n",
+      "1141/2707\n",
+      "1142/2707\n",
+      "Audio time = 3.17 sec.\n",
+      "Recognition time = 9.915915966033936 sec.\n",
+      "生活中不致影响我们所需时间\n",
+      "生物钟不只影响我们的作息时间\n",
+      "1143/2707\n",
+      "1144/2707\n",
+      "1145/2707\n",
+      "1146/2707\n",
+      "Audio time = 2.52 sec.\n",
+      "Recognition time = 10.053148984909058 sec.\n",
+      "还有我们的方方面面\n",
+      "还有我们的方方面面\n",
+      "1147/2707\n",
+      "1148/2707\n",
+      "1149/2707\n",
+      "1150/2707\n",
+      "Audio time = 3.63 sec.\n",
+      "Recognition time = 10.035830974578857 sec.\n",
+      "比如说我们的体温心率\n",
+      "比如说我们的体温 心率\n",
+      "1151/2707\n",
+      "1152/2707\n",
+      "1153/2707\n",
+      "1154/2707\n",
+      "Audio time = 2.22 sec.\n",
+      "Recognition time = 9.93106198310852 sec.\n",
+      "我们的这个血压\n",
+      "我们的血压\n",
+      "1155/2707\n",
+      "1156/2707\n",
+      "1157/2707\n",
+      "1158/2707\n",
+      "1159/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 10.936872959136963 sec.\n",
+      "都有二零四小时的戒律\n",
+      "都有24小时的节律\n",
+      "1160/2707\n",
+      "1161/2707\n",
+      "1162/2707\n",
+      "1163/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 9.996380805969238 sec.\n",
+      "生物钟索取中我就重按十四小时在竭力\n",
+      "生物钟所驱动的这种24小时的节律\n",
+      "1164/2707\n",
+      "1165/2707\n",
+      "1166/2707\n",
+      "1167/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.605979919433594 sec.\n",
+      "我们把它称为今日戒律\n",
+      "我们把它称为近日节律\n",
+      "1168/2707\n",
+      "1169/2707\n",
+      "1170/2707\n",
+      "1171/2707\n",
+      "Audio time = 4.12 sec.\n",
+      "Recognition time = 9.11269497871399 sec.\n",
+      "就是大约翌日大约二里四小时的个意思\n",
+      "就是大约一日 大约24小时的意思\n",
+      "1172/2707\n",
+      "1173/2707\n",
+      "1174/2707\n",
+      "1175/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 9.989053964614868 sec.\n",
+      "他还有一个更为同属\n",
+      "它还有一个更为通俗\n",
+      "1176/2707\n",
+      "1177/2707\n",
+      "1178/2707\n",
+      "1179/2707\n",
+      "Audio time = 2.65 sec.\n",
+      "Recognition time = 11.103986263275146 sec.\n",
+      "但是不那么准确的称呼\n",
+      "但是不那么准确的称呼\n",
+      "1180/2707\n",
+      "1181/2707\n",
+      "1182/2707\n",
+      "1183/2707\n",
+      "Audio time = 2.02 sec.\n",
+      "Recognition time = 9.995306968688965 sec.\n",
+      "我叫做昼夜节律\n",
+      "叫做昼夜节律\n",
+      "1184/2707\n",
+      "1185/2707\n",
+      "1186/2707\n",
+      "1187/2707\n",
+      "Audio time = 3.55 sec.\n",
+      "Recognition time = 10.177406072616577 sec.\n",
+      "我们生物钟与今日戒律在地球上\n",
+      "生物钟与近日节律在地球上\n",
+      "1188/2707\n",
+      "1189/2707\n",
+      "1190/2707\n",
+      "1191/2707\n",
+      "Audio time = 3.52 sec.\n",
+      "Recognition time = 9.945289134979248 sec.\n",
+      "大概七十一年词可能就出现了\n",
+      "大概几十亿年前可能就出现了\n",
+      "1192/2707\n",
+      "1193/2707\n",
+      "1194/2707\n",
+      "1195/2707\n",
+      "Audio time = 4.4 sec.\n",
+      "Recognition time = 9.958027839660645 sec.\n",
+      "从最肩带的意中人和代谢宝生物\n",
+      "从最简单的一种单细胞生物\n",
+      "1196/2707\n",
+      "1197/2707\n",
+      "1198/2707\n",
+      "1199/2707\n",
+      "Audio time = 1.85 sec.\n",
+      "Recognition time = 9.92228889465332 sec.\n",
+      "比如来细菌\n",
+      "比如蓝细菌\n",
+      "1200/2707\n",
+      "1201/2707\n",
+      "1202/2707\n",
+      "1203/2707\n",
+      "Audio time = 2.73 sec.\n",
+      "Recognition time = 9.189191818237305 sec.\n",
+      "就是图上这个绿绿的东西\n",
+      "就是图上这个绿绿的东西\n",
+      "1204/2707\n",
+      "1205/2707\n",
+      "1206/2707\n",
+      "1207/2707\n",
+      "Audio time = 4.3 sec.\n",
+      "Recognition time = 9.890074253082275 sec.\n",
+      "一直到各种复杂的植物动物\n",
+      "一直到各种复杂的植物 动物\n",
+      "1208/2707\n",
+      "1209/2707\n",
+      "1210/2707\n",
+      "1211/2707\n",
+      "Audio time = 3.17 sec.\n",
+      "Recognition time = 10.07413911819458 sec.\n",
+      "都能生物钟和今日戒律\n",
+      "都有生物钟和近日节律\n",
+      "1212/2707\n",
+      "1213/2707\n",
+      "1214/2707\n",
+      "1215/2707\n",
+      "Audio time = 4.47 sec.\n",
+      "Recognition time = 10.444883108139038 sec.\n",
+      "所以说它其实是一种比睡眠要古老得多的现象\n",
+      "所以它其实是一种比睡眠要古老得多的现象\n",
+      "1216/2707\n",
+      "1217/2707\n",
+      "1218/2707\n",
+      "1219/2707\n",
+      "Audio time = 3.67 sec.\n",
+      "Recognition time = 10.546808004379272 sec.\n",
+      "这个其实也挺合理挺容易理解的因为\n",
+      "这个其实也挺合理 挺容易理解的\n",
+      "1220/2707\n",
+      "1221/2707\n",
+      "1222/2707\n",
+      "1223/2707\n",
+      "Audio time = 3.06 sec.\n",
+      "Recognition time = 10.138069868087769 sec.\n",
+      "因睡眠只是生活中调控的\n",
+      "因为睡眠只是生物钟调控的\n",
+      "1224/2707\n",
+      "1225/2707\n",
+      "1226/2707\n",
+      "1227/2707\n",
+      "Audio time = 3.87 sec.\n",
+      "Recognition time = 11.620110034942627 sec.\n",
+      "帮户数个生命过程中间的一个\n",
+      "无数个生命过程中间的一个\n",
+      "1228/2707\n",
+      "1229/2707\n",
+      "1230/2707\n",
+      "1231/2707\n",
+      "Audio time = 2.6 sec.\n",
+      "Recognition time = 10.32073712348938 sec.\n",
+      "在分子呈面道声中\n",
+      "在分子层面\n",
+      "1232/2707\n",
+      "1233/2707\n",
+      "1234/2707\n",
+      "1235/2707\n",
+      "Audio time = 4.8 sec.\n",
+      "Recognition time = 10.453410148620605 sec.\n",
+      "生物钟是有大概十几个基因组成的一个反馈环路\n",
+      "生物钟是由大概十几个基因组成的一个反馈环路\n",
+      "1236/2707\n",
+      "1237/2707\n",
+      "1238/2707\n",
+      "1239/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 9.99799394607544 sec.\n",
+      "去年的诺被生理医学奖\n",
+      "去年的诺贝尔生理医学奖\n",
+      "1240/2707\n",
+      "1241/2707\n",
+      "1242/2707\n",
+      "1243/2707\n",
+      "Audio time = 4.47 sec.\n",
+      "Recognition time = 10.13641095161438 sec.\n",
+      "就颁给了三位再过瘾克隆出\n",
+      "就颁给了三位在果蝇里克隆出\n",
+      "1244/2707\n",
+      "1245/2707\n",
+      "1246/2707\n",
+      "1247/2707\n",
+      "Audio time = 2.9 sec.\n",
+      "Recognition time = 10.239814043045044 sec.\n",
+      "除第一个生物中浸淫的科学家\n",
+      "第一个生物钟基因的科学家\n",
+      "1248/2707\n",
+      "1249/2707\n",
+      "1250/2707\n",
+      "1251/2707\n",
+      "Audio time = 3.13 sec.\n",
+      "Recognition time = 10.1371910572052 sec.\n",
+      "国营改天轮仅在哺乳动物\n",
+      "果蝇的period基因在哺乳动物\n",
+      "1252/2707\n",
+      "1253/2707\n",
+      "1254/2707\n",
+      "1255/2707\n",
+      "Audio time = 2.67 sec.\n",
+      "Recognition time = 10.2382173538208 sec.\n",
+      "动物包括我们人类便是由三个\n",
+      "包括我们人里面是有3个\n",
+      "1256/2707\n",
+      "1257/2707\n",
+      "1258/2707\n",
+      "1259/2707\n",
+      "Audio time = 4.27 sec.\n",
+      "Recognition time = 10.138260841369629 sec.\n",
+      "分别叫做平人玩味秋荷亭为思维\n",
+      "分别叫做PER1 PER2和PER3\n",
+      "1260/2707\n",
+      "1261/2707\n",
+      "1262/2707\n",
+      "1263/2707\n",
+      "Audio time = 3.48 sec.\n",
+      "Recognition time = 10.067363977432251 sec.\n",
+      "这个就是我前面讲到的\n",
+      "PER2这个就是我前面讲到的\n",
+      "1264/2707\n",
+      "1265/2707\n",
+      "1266/2707\n",
+      "1267/2707\n",
+      "Audio time = 4.62 sec.\n",
+      "Recognition time = 10.411110162734985 sec.\n",
+      "他的便也导致了大家出入的气度的早睡早起\n",
+      "它的变异导致了那个大家族极度的早睡早起\n",
+      "1268/2707\n",
+      "1269/2707\n",
+      "1270/2707\n",
+      "1271/2707\n",
+      "Audio time = 4.8 sec.\n",
+      "Recognition time = 10.434869050979614 sec.\n",
+      "然后我们实验室研究的方向是这个可司机\n",
+      "我们实验室研究的方向是PER3基因\n",
+      "1272/2707\n",
+      "1273/2707\n",
+      "1274/2707\n",
+      "1275/2707\n",
+      "Audio time = 4.32 sec.\n",
+      "Recognition time = 10.863201141357422 sec.\n",
+      "我们发现会碎金的汉奸便也\n",
+      "我们发现PER3基因的罕见变异\n",
+      "1276/2707\n",
+      "1277/2707\n",
+      "1278/2707\n",
+      "1279/2707\n",
+      "Audio time = 4.1 sec.\n",
+      "Recognition time = 10.445040225982666 sec.\n",
+      "爷爷可以捯饬人气度的早睡早起\n",
+      "也可以导致人极度地早睡早起\n",
+      "1280/2707\n",
+      "1281/2707\n",
+      "1282/2707\n",
+      "1283/2707\n",
+      "Audio time = 2.35 sec.\n",
+      "Recognition time = 9.75477385520935 sec.\n",
+      "除了早睡早起\n",
+      "除了早睡早起\n",
+      "1284/2707\n",
+      "1285/2707\n",
+      "1286/2707\n",
+      "1287/2707\n",
+      "Audio time = 3.1 sec.\n",
+      "Recognition time = 10.007096767425537 sec.\n",
+      "他们还有一种情绪病\n",
+      "他们还有一种情绪病\n",
+      "1288/2707\n",
+      "1289/2707\n",
+      "1290/2707\n",
+      "1291/2707\n",
+      "Audio time = 3.08 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 10.24026894569397 sec.\n",
+      "叫做季节性情感障碍\n",
+      "叫做季节性情感障碍\n",
+      "1292/2707\n",
+      "1293/2707\n",
+      "1294/2707\n",
+      "1295/2707\n",
+      "Audio time = 2.52 sec.\n",
+      "Recognition time = 9.906393051147461 sec.\n",
+      "俗称东徙倚欲\n",
+      "俗称冬季抑郁\n",
+      "1296/2707\n",
+      "1297/2707\n",
+      "1298/2707\n",
+      "1299/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 10.47254991531372 sec.\n",
+      "这个病的主要特征就是\n",
+      "这个病的主要特征就是\n",
+      "1300/2707\n",
+      "1301/2707\n",
+      "1302/2707\n",
+      "1303/2707\n",
+      "Audio time = 5.93 sec.\n",
+      "Recognition time = 10.54602599143982 sec.\n",
+      "就是患者在每年的秋天会开始出现一些抑郁的症状\n",
+      "患者在每年的秋天会开始出现一些抑郁的症状\n",
+      "1304/2707\n",
+      "1305/2707\n",
+      "1306/2707\n",
+      "1307/2707\n",
+      "Audio time = 4.45 sec.\n",
+      "Recognition time = 9.978378057479858 sec.\n",
+      "然后到冬天冻气的时候是最严重的\n",
+      "然后到冬季的时候是最严重的\n",
+      "1308/2707\n",
+      "1309/2707\n",
+      "1310/2707\n",
+      "1311/2707\n",
+      "Audio time = 3.72 sec.\n",
+      "Recognition time = 10.40015697479248 sec.\n",
+      "渠道每年十二月一月二月的时候是随眼中的\n",
+      "就到每年12月 1月 2月的时候是最严重的\n",
+      "1312/2707\n",
+      "1313/2707\n",
+      "1314/2707\n",
+      "1315/2707\n",
+      "Audio time = 3.75 sec.\n",
+      "Recognition time = 10.24106478691101 sec.\n",
+      "然后到次年的春夏优惠此法的好准\n",
+      "然后到次年的春夏又会自发地好转\n",
+      "1316/2707\n",
+      "1317/2707\n",
+      "1318/2707\n",
+      "1319/2707\n",
+      "Audio time = 4.06 sec.\n",
+      "Recognition time = 10.237606048583984 sec.\n",
+      "就是这一些性感障碍她在人群中的发病率\n",
+      "季节性情感障碍它在人群中的发病率\n",
+      "1320/2707\n",
+      "1321/2707\n",
+      "1322/2707\n",
+      "1323/2707\n",
+      "Audio time = 2.98 sec.\n",
+      "Recognition time = 10.341224908828735 sec.\n",
+      "并屡遇大概是百分之一到百分之十\n",
+      "大概是1%到10%\n",
+      "1324/2707\n",
+      "1325/2707\n",
+      "1326/2707\n",
+      "1327/2707\n",
+      "Audio time = 3.93 sec.\n",
+      "Recognition time = 10.03522515296936 sec.\n",
+      "所以这些这个现象就提示我们\n",
+      "这个现象就提示我们\n",
+      "1328/2707\n",
+      "1329/2707\n",
+      "1330/2707\n",
+      "1331/2707\n",
+      "Audio time = 3.31 sec.\n",
+      "Recognition time = 10.137287855148315 sec.\n",
+      "我们生物钟和今日竭力的紊乱\n",
+      "生物钟和近日节律的紊乱\n",
+      "1332/2707\n",
+      "1333/2707\n",
+      "1334/2707\n",
+      "1335/2707\n",
+      "Audio time = 3.74 sec.\n",
+      "Recognition time = 9.831539869308472 sec.\n",
+      "卵可能与精神疾病也有关联\n",
+      "可能与精神疾病也有关联\n",
+      "1336/2707\n",
+      "1337/2707\n",
+      "1338/2707\n",
+      "1339/2707\n",
+      "Audio time = 2.85 sec.\n",
+      "Recognition time = 10.23816204071045 sec.\n",
+      "前面我给大家讲了两个都是\n",
+      "前面我给大家讲了两个\n",
+      "1340/2707\n",
+      "1341/2707\n",
+      "1342/2707\n",
+      "1343/2707\n",
+      "Audio time = 4.55 sec.\n",
+      "Recognition time = 10.233273983001709 sec.\n",
+      "两个都是这种白领聊性的扫雪早期的别一\n",
+      "都是这种百灵鸟型的早睡早起的变异\n",
+      "1344/2707\n",
+      "1345/2707\n",
+      "1346/2707\n",
+      "1347/2707\n",
+      "Audio time = 5.33 sec.\n",
+      "Recognition time = 9.019546747207642 sec.\n",
+      "还有这种变异人是可以导致有夜猫子型的作息\n",
+      "还有变异是可以导致夜猫子型的作息\n",
+      "1348/2707\n",
+      "1349/2707\n",
+      "1350/2707\n",
+      "1351/2707\n",
+      "Audio time = 3.64 sec.\n",
+      "Recognition time = 8.906440734863281 sec.\n",
+      "比如说美国的科研人员发现在这个叫做\n",
+      "比如说美国的科研人员发现在这个\n",
+      "1352/2707\n",
+      "1353/2707\n",
+      "1354/2707\n",
+      "1355/2707\n",
+      "Audio time = 4.76 sec.\n",
+      "Recognition time = 10.03446912765503 sec.\n",
+      "在这个叫做头颇不安的生活中基因里面的变异\n",
+      "叫做CRYPTOCHROME1生物钟基因里面的变异\n",
+      "1356/2707\n",
+      "1357/2707\n",
+      "1358/2707\n",
+      "1359/2707\n",
+      "Audio time = 3.35 sec.\n",
+      "Recognition time = 10.754530191421509 sec.\n",
+      "就可以逃至人嫉妒的顽石晚期\n",
+      "就可以导致人极度地晚睡晚起\n",
+      "1360/2707\n",
+      "1361/2707\n",
+      "1362/2707\n",
+      "1363/2707\n",
+      "Audio time = 4.87 sec.\n",
+      "Recognition time = 9.2134850025177 sec.\n",
+      "其实人群中夜猫子型的作息是比白领狼性的要多的\n",
+      "其实人群中夜猫子型的作息是比百灵鸟型的要多的\n",
+      "1364/2707\n",
+      "1365/2707\n",
+      "1366/2707\n",
+      "1367/2707\n",
+      "Audio time = 2.87 sec.\n",
+      "Recognition time = 9.932822942733765 sec.\n",
+      "在这其中了有一部分事项\n",
+      "但是其中有一部分是像\n",
+      "1368/2707\n",
+      "1369/2707\n",
+      "1370/2707\n",
+      "1371/2707\n",
+      "Audio time = 3.83 sec.\n",
+      "Recognition time = 9.010280847549438 sec.\n",
+      "带了个多矿完井便衣的人一样\n",
+      "带了CRYPTOCHROME1基因变异的人一样\n",
+      "1372/2707\n",
+      "1373/2707\n",
+      "1374/2707\n",
+      "1375/2707\n",
+      "Audio time = 3.37 sec.\n",
+      "Recognition time = 9.039043664932251 sec.\n",
+      "一样是因为一些起因变异导致的\n",
+      "是因为一些基因变异导致的\n",
+      "1376/2707\n",
+      "1377/2707\n",
+      "1378/2707\n",
+      "1379/2707\n",
+      "Audio time = 4.03 sec.\n",
+      "Recognition time = 10.82593584060669 sec.\n",
+      "但是还有一些可能是为环境因素导致的\n",
+      "但是还有一些可能是因为环境因素导致的\n",
+      "1380/2707\n",
+      "1381/2707\n",
+      "1382/2707\n",
+      "1383/2707\n",
+      "Audio time = 2.7 sec.\n",
+      "Recognition time = 8.912533044815063 sec.\n",
+      "比如说你晚上七时一定很困了\n",
+      "比如说你晚上其实已经很困了\n",
+      "1384/2707\n",
+      "1385/2707\n",
+      "1386/2707\n",
+      "1387/2707\n",
+      "Audio time = 4.25 sec.\n",
+      "Recognition time = 9.007572889328003 sec.\n",
+      "但是还想玩有心想看片不想睡觉\n",
+      "但是还想玩游戏 想看片 不想睡觉\n",
+      "1388/2707\n",
+      "1389/2707\n",
+      "1390/2707\n",
+      "1391/2707\n",
+      "Audio time = 4.38 sec.\n",
+      "Recognition time = 8.792241334915161 sec.\n",
+      "这也是这个椰汁晚睡晚起的檐帽的星座性\n",
+      "这个也是晚睡晚起的夜猫子型作息\n",
+      "1392/2707\n",
+      "1393/2707\n",
+      "1394/2707\n",
+      "1395/2707\n",
+      "Audio time = 2.72 sec.\n",
+      "Recognition time = 8.819468021392822 sec.\n",
+      "作息但是并不是天生的\n",
+      "但是并不是天生的\n",
+      "1396/2707\n",
+      "1397/2707\n",
+      "1398/2707\n",
+      "1399/2707\n",
+      "Audio time = 3.52 sec.\n",
+      "Recognition time = 9.148534059524536 sec.\n",
+      "虽然说生物钟天生的变异\n",
+      "虽然说生物钟天生的变异\n",
+      "1400/2707\n",
+      "1401/2707\n",
+      "1402/2707\n",
+      "1403/2707\n",
+      "Audio time = 4.23 sec.\n",
+      "Recognition time = 8.976423978805542 sec.\n",
+      "可以导致我们个体之间生活中的差异\n",
+      "可以导致我们个体之间生物钟的差异\n",
+      "1404/2707\n",
+      "1405/2707\n",
+      "1406/2707\n",
+      "1407/2707\n",
+      "Audio time = 4.25 sec.\n",
+      "Recognition time = 10.136827945709229 sec.\n",
+      "但是生活中的差异的也不全是天生的\n",
+      "但是生物钟的差异也不全是天生的\n",
+      "1408/2707\n",
+      "1409/2707\n",
+      "1410/2707\n",
+      "1411/2707\n",
+      "Audio time = 2.18 sec.\n",
+      "Recognition time = 9.944804906845093 sec.\n",
+      "就是同一个人\n",
+      "就是同一个人\n",
+      "1412/2707\n",
+      "1413/2707\n",
+      "1414/2707\n",
+      "1415/2707\n",
+      "Audio time = 3.1199375 sec.\n",
+      "Recognition time = 10.124817848205566 sec.\n",
+      "一人他在年轻和年老的时候\n",
+      "他在年轻和年老的时候\n",
+      "1416/2707\n",
+      "1417/2707\n",
+      "1418/2707\n",
+      "1419/2707\n",
+      "Audio time = 2.5799375 sec.\n",
+      "Recognition time = 10.136040925979614 sec.\n",
+      "后海的生活中也是不一样的\n",
+      "他的生物钟也是不一样的\n",
+      "1420/2707\n",
+      "1421/2707\n",
+      "1422/2707\n",
+      "1423/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 10.605434894561768 sec.\n",
+      "新恋人特别是十几岁的青少年\n",
+      "青年人 特别是十几岁的青少年\n",
+      "1424/2707\n",
+      "1425/2707\n",
+      "1426/2707\n",
+      "1427/2707\n",
+      "Audio time = 4.4000625 sec.\n",
+      "Recognition time = 9.873936891555786 sec.\n",
+      "而这生物钟是更加倾向于晚睡晚起的\n",
+      "他的生物钟是更加倾向于晚睡晚起的\n",
+      "1428/2707\n",
+      "1429/2707\n",
+      "1430/2707\n",
+      "1431/2707\n",
+      "Audio time = 3.15 sec.\n",
+      "Recognition time = 9.713008165359497 sec.\n",
+      "由于也就是大家可能会想到的\n",
+      "有一点就是大家可能会想到的\n",
+      "1432/2707\n",
+      "1433/2707\n",
+      "1434/2707\n",
+      "1435/2707\n",
+      "Audio time = 4.4499375 sec.\n",
+      "Recognition time = 10.459751844406128 sec.\n",
+      "其实青少年他每天早上上学的时间还挺早的\n",
+      "其实青少年每天早上上学的时间还挺早的\n",
+      "1436/2707\n",
+      "1437/2707\n",
+      "1438/2707\n",
+      "1439/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 10.139230012893677 sec.\n",
+      "把电动稳婆的是七点半深圳市更早\n",
+      "8点钟或者是7点半 甚至是更早\n",
+      "1440/2707\n",
+      "1441/2707\n",
+      "1442/2707\n",
+      "1443/2707\n",
+      "Audio time = 4.3 sec.\n",
+      "Recognition time = 13.473580837249756 sec.\n",
+      "所以其实就是说现在目前我们这种上学的事\n",
+      "这其实就是说现在目前这种上学的时间\n",
+      "1444/2707\n",
+      "1445/2707\n",
+      "1446/2707\n",
+      "1447/2707\n",
+      "Audio time = 5.2 sec.\n",
+      "Recognition time = 11.407232999801636 sec.\n",
+      "事事要强薄衣裙夜猫子型天生的夜猫子型的青年人\n",
+      "是要强迫一群天生的夜猫子型的青年人\n",
+      "1448/2707\n",
+      "1449/2707\n",
+      "1450/2707\n",
+      "1451/2707\n",
+      "Audio time = 3.23 sec.\n",
+      "Recognition time = 10.145721197128296 sec.\n",
+      "去要强过他们早学早七\n",
+      "要强迫他们早睡早起\n",
+      "1452/2707\n",
+      "1453/2707\n",
+      "1454/2707\n",
+      "1455/2707\n",
+      "Audio time = 2.95 sec.\n",
+      "Recognition time = 9.852151870727539 sec.\n",
+      "这对于他们其实是挺痛苦的\n",
+      "这对于他们其实是挺痛苦的\n",
+      "1456/2707\n",
+      "1457/2707\n",
+      "1458/2707\n",
+      "1459/2707\n",
+      "Audio time = 4.13 sec.\n",
+      "Recognition time = 10.926384925842285 sec.\n",
+      "而且对他们的健康也不是太有利\n",
+      "而且对他们的健康也不是太有利\n",
+      "1460/2707\n",
+      "1461/2707\n",
+      "1462/2707\n",
+      "1463/2707\n",
+      "Audio time = 5.1 sec.\n",
+      "Recognition time = 10.752143144607544 sec.\n",
+      "所以现在国外的一些学校\n",
+      "所以现在国外的一些学校\n",
+      "1464/2707\n",
+      "1465/2707\n",
+      "1466/2707\n",
+      "1467/2707\n",
+      "Audio time = 8.1 sec.\n",
+      "Recognition time = 10.927308082580566 sec.\n",
+      "就是开始时请让中学更晚的开课的时间看是上课的这件更管\n",
+      "开始试行让中学开始上课的时间更晚\n",
+      "1468/2707\n",
+      "1469/2707\n",
+      "1470/2707\n",
+      "1471/2707\n",
+      "Audio time = 4.58 sec.\n",
+      "Recognition time = 11.397500038146973 sec.\n",
+      "他们认为这个可能会更有利于这些学生的健康\n",
+      "他们认为这个可能会更有利于这些学生的健康\n",
+      "1472/2707\n",
+      "1473/2707\n",
+      "1474/2707\n",
+      "1475/2707\n",
+      "Audio time = 3.35 sec.\n",
+      "Recognition time = 10.715612888336182 sec.\n",
+      "以期他们的认知表现\n",
+      "以及他们的认知表现\n",
+      "1476/2707\n",
+      "1477/2707\n",
+      "1478/2707\n",
+      "1479/2707\n",
+      "Audio time = 2.45 sec.\n",
+      "Recognition time = 9.560259103775024 sec.\n",
+      "就是说他们在学习长街\n",
+      "也就是说他们的学习成绩\n",
+      "1480/2707\n",
+      "1481/2707\n",
+      "1482/2707\n",
+      "1483/2707\n",
+      "Audio time = 5.17 sec.\n",
+      "Recognition time = 11.77139401435852 sec.\n",
+      "所以如果你的孩子在学校上课的时候谁笑了\n",
+      "所以如果你的孩子在学校上课的时候睡着了\n",
+      "1484/2707\n",
+      "1485/2707\n",
+      "1486/2707\n",
+      "1487/2707\n",
+      "Audio time = 2.2 sec.\n",
+      "Recognition time = 9.419704914093018 sec.\n",
+      "清理原谅他\n",
+      "请你原谅他\n",
+      "1488/2707\n",
+      "1489/2707\n",
+      "1490/2707\n",
+      "1491/2707\n",
+      "Audio time = 3.03 sec.\n",
+      "Recognition time = 11.073076009750366 sec.\n",
+      "这个也不一定她就是不认真\n",
+      "这个也不一定他就是不认真\n",
+      "1492/2707\n",
+      "1493/2707\n",
+      "1494/2707\n",
+      "1495/2707\n",
+      "Audio time = 3.55 sec.\n",
+      "Recognition time = 10.228187799453735 sec.\n",
+      "它也可能是因为他的生物钟中导致的\n",
+      "它也可能是因为他的生物钟导致的\n",
+      "1496/2707\n",
+      "1497/2707\n",
+      "1498/2707\n",
+      "1499/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 10.161854982376099 sec.\n",
+      "到这里我就小结了一下\n",
+      "到这里我就小结一下\n",
+      "1500/2707\n",
+      "1501/2707\n",
+      "1502/2707\n",
+      "1503/2707\n",
+      "Audio time = 2.57 sec.\n",
+      "Recognition time = 10.001413822174072 sec.\n",
+      "我倒不亲卫一直讲的内容\n",
+      "我到目前为止讲的内容\n",
+      "1504/2707\n",
+      "1505/2707\n",
+      "1506/2707\n",
+      "1507/2707\n",
+      "Audio time = 4.45 sec.\n",
+      "Recognition time = 8.813225984573364 sec.\n",
+      "所以睡眠其实是主要通过两个同入\n",
+      "睡眠其实是主要通过两个通路\n",
+      "1508/2707\n",
+      "1509/2707\n",
+      "1510/2707\n",
+      "1511/2707\n",
+      "Audio time = 3.35 sec.\n",
+      "Recognition time = 9.932440042495728 sec.\n",
+      "或者说两股力量来调控的\n",
+      "或者说两股力量来调控的\n",
+      "1512/2707\n",
+      "1513/2707\n",
+      "1514/2707\n",
+      "1515/2707\n",
+      "Audio time = 2.73 sec.\n",
+      "Recognition time = 9.561797142028809 sec.\n",
+      "一个就是我们的生活中\n",
+      "一个就是我们的生物钟\n",
+      "1516/2707\n",
+      "1517/2707\n",
+      "1518/2707\n",
+      "1519/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 9.894231796264648 sec.\n",
+      "还有一个就是我前面提到了我太平衡\n",
+      "还有一个就是我前面提到的稳态平衡\n",
+      "1520/2707\n",
+      "1521/2707\n",
+      "1522/2707\n",
+      "1523/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 8.629566431045532 sec.\n",
+      "生活种种决定的是我们什么时候睡\n",
+      "生物钟决定的是我们什么时候睡\n",
+      "1524/2707\n",
+      "1525/2707\n",
+      "1526/2707\n",
+      "1527/2707\n",
+      "Audio time = 5.03 sec.\n",
+      "Recognition time = 9.865908861160278 sec.\n",
+      "而我太平和决定的是我们睡多久睡多深\n",
+      "而稳态平衡决定的是我们睡多久 睡多深\n",
+      "1528/2707\n",
+      "1529/2707\n",
+      "1530/2707\n",
+      "1531/2707\n",
+      "Audio time = 3.67 sec.\n",
+      "Recognition time = 10.085025072097778 sec.\n",
+      "听到这里可能会有观众想\n",
+      "听到这里可能会有观众想\n",
+      "1532/2707\n",
+      "1533/2707\n",
+      "1534/2707\n",
+      "1535/2707\n",
+      "Audio time = 4.43 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 9.738590955734253 sec.\n",
+      "试听了很多道理但是还是睡不了一个好觉\n",
+      "是听了很多道理 但是还是睡不了一个好觉\n",
+      "1536/2707\n",
+      "1537/2707\n",
+      "1538/2707\n",
+      "1539/2707\n",
+      "Audio time = 6.68 sec.\n",
+      "Recognition time = 11.137609958648682 sec.\n",
+      "所以就接下来的和大家聊一下一些广为流传的盖上\n",
+      "所以接下来和大家聊一下一些广为流传的\n",
+      "1540/2707\n",
+      "1541/2707\n",
+      "1542/2707\n",
+      "1543/2707\n",
+      "Audio time = 2.97 sec.\n",
+      "Recognition time = 10.444470167160034 sec.\n",
+      "改善或者促进睡眠的一些方法\n",
+      "改善或者促进睡眠的一些方法\n",
+      "1544/2707\n",
+      "1545/2707\n",
+      "1546/2707\n",
+      "1547/2707\n",
+      "Audio time = 2.4 sec.\n",
+      "Recognition time = 9.709181070327759 sec.\n",
+      "他们是不是真的有效\n",
+      "它们是不是真的有效\n",
+      "1548/2707\n",
+      "1549/2707\n",
+      "1550/2707\n",
+      "1551/2707\n",
+      "Audio time = 5.37 sec.\n",
+      "Recognition time = 10.36344313621521 sec.\n",
+      "大家可能都是听说过就是喝牛奶可以促进睡眠\n",
+      "大家可能都听说过喝牛奶可以促进睡眠\n",
+      "1552/2707\n",
+      "1553/2707\n",
+      "1554/2707\n",
+      "1555/2707\n",
+      "Audio time = 3.68 sec.\n",
+      "Recognition time = 9.31540298461914 sec.\n",
+      "喝着来是不是真的可以促进睡眠呢\n",
+      "喝牛奶是不是真的可以促进睡眠呢\n",
+      "1556/2707\n",
+      "1557/2707\n",
+      "1558/2707\n",
+      "1559/2707\n",
+      "Audio time = 3.87 sec.\n",
+      "Recognition time = 10.648298978805542 sec.\n",
+      "牛奶以及其它的一切乳制品里面\n",
+      "牛奶以及其他的一些乳制品里面\n",
+      "1560/2707\n",
+      "1561/2707\n",
+      "1562/2707\n",
+      "1563/2707\n",
+      "Audio time = 3.08 sec.\n",
+      "Recognition time = 9.419909954071045 sec.\n",
+      "还有一种叫做四爱酸的物质\n",
+      "含有一种叫做色氨酸的物质\n",
+      "1564/2707\n",
+      "1565/2707\n",
+      "1566/2707\n",
+      "1567/2707\n",
+      "Audio time = 5.3 sec.\n",
+      "Recognition time = 10.75905990600586 sec.\n",
+      "后者中文字一点程度上是可以改善和促进睡眠的\n",
+      "这种物质一定程度上是可以改善和促进睡眠的\n",
+      "1568/2707\n",
+      "1569/2707\n",
+      "1570/2707\n",
+      "1571/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.62932014465332 sec.\n",
+      "但是他不知纽带利率诶有\n",
+      "但是它不只牛奶里面有\n",
+      "1572/2707\n",
+      "1573/2707\n",
+      "1574/2707\n",
+      "1575/2707\n",
+      "Audio time = 6.5 sec.\n",
+      "Recognition time = 11.174374103546143 sec.\n",
+      "在蛋类鱼类肉类打动类产品中也都富含色胺孙\n",
+      "在蛋类 鱼类 肉类 大豆类产品中也都富含色氨酸\n",
+      "1576/2707\n",
+      "1577/2707\n",
+      "1578/2707\n",
+      "1579/2707\n",
+      "Audio time = 4.43 sec.\n",
+      "Recognition time = 10.775142908096313 sec.\n",
+      "然后经典流行一种叫做水便溏的东东\n",
+      "近年流行一种叫做睡眠糖的东东\n",
+      "1580/2707\n",
+      "1581/2707\n",
+      "1582/2707\n",
+      "1583/2707\n",
+      "Audio time = 3.1 sec.\n",
+      "Recognition time = 10.631054162979126 sec.\n",
+      "然后据说是可以促进睡眠\n",
+      "据说是可以促进睡眠\n",
+      "1584/2707\n",
+      "1585/2707\n",
+      "1586/2707\n",
+      "1587/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 11.988529205322266 sec.\n",
+      "这个睡眠唐诗什么的\n",
+      "这个睡眠糖是什么呢\n",
+      "1588/2707\n",
+      "1589/2707\n",
+      "1590/2707\n",
+      "1591/2707\n",
+      "Audio time = 4.48 sec.\n",
+      "Recognition time = 8.991067886352539 sec.\n",
+      "它的主要成分其实就是推诿苏\n",
+      "它的主要成分其实就是褪黑素\n",
+      "1592/2707\n",
+      "1593/2707\n",
+      "1594/2707\n",
+      "1595/2707\n",
+      "Audio time = 5.13 sec.\n",
+      "Recognition time = 10.789504051208496 sec.\n",
+      "然后推着此事当中我们条件生物钟的\n",
+      "褪黑素是帮助我们调节生物钟的\n",
+      "1596/2707\n",
+      "1597/2707\n",
+      "1598/2707\n",
+      "1599/2707\n",
+      "1600/2707\n",
+      "Audio time = 3.37 sec.\n",
+      "Recognition time = 10.617730140686035 sec.\n",
+      "他可能以丁城都可以帮助改善睡眠\n",
+      "它可能一定程度可以帮助改善睡眠\n",
+      "1601/2707\n",
+      "1602/2707\n",
+      "1603/2707\n",
+      "1604/2707\n",
+      "Audio time = 4.7 sec.\n",
+      "Recognition time = 10.75219202041626 sec.\n",
+      "但是它最主要的功效是保住我们倒时差\n",
+      "但是它最主要的功效是帮助我们倒时差\n",
+      "1605/2707\n",
+      "1606/2707\n",
+      "1607/2707\n",
+      "1608/2707\n",
+      "Audio time = 3.75 sec.\n",
+      "Recognition time = 10.23914909362793 sec.\n",
+      "而且这个效果也还是因人而低的\n",
+      "而且这个效果也还是因人而异的\n",
+      "1609/2707\n",
+      "1610/2707\n",
+      "1611/2707\n",
+      "1612/2707\n",
+      "Audio time = 2.37 sec.\n",
+      "Recognition time = 11.262695074081421 sec.\n",
+      "在我们小的时候睡不消\n",
+      "在我们小的时候睡不着\n",
+      "1613/2707\n",
+      "1614/2707\n",
+      "1615/2707\n",
+      "1616/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 10.642468690872192 sec.\n",
+      "把妈妈都会说谁不知可以属羊\n",
+      "爸爸妈妈都会说睡不着可以数羊\n",
+      "1617/2707\n",
+      "1618/2707\n",
+      "1619/2707\n",
+      "1620/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 11.168534994125366 sec.\n",
+      "数量神不是真的可以帮助你入睡的\n",
+      "数羊是不是真的可以帮助你入睡呢\n",
+      "1621/2707\n",
+      "1622/2707\n",
+      "1623/2707\n",
+      "1624/2707\n",
+      "Audio time = 3.33 sec.\n",
+      "Recognition time = 9.928301095962524 sec.\n",
+      "如果说你在熟料的过程中\n",
+      "如果说你在数羊的过程中\n",
+      "1625/2707\n",
+      "1626/2707\n",
+      "1627/2707\n",
+      "1628/2707\n",
+      "Audio time = 2.87 sec.\n",
+      "Recognition time = 8.661370038986206 sec.\n",
+      "他确实会让你干变到更放松\n",
+      "它确实会让你感觉到更放松\n",
+      "1629/2707\n",
+      "1630/2707\n",
+      "1631/2707\n",
+      "1632/2707\n",
+      "Audio time = 2.68 sec.\n",
+      "Recognition time = 9.568925142288208 sec.\n",
+      "帮助你的肌肉放松\n",
+      "帮助你的肌肉放松\n",
+      "1633/2707\n",
+      "1634/2707\n",
+      "1635/2707\n",
+      "1636/2707\n",
+      "1637/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 9.830211162567139 sec.\n",
+      "它一定程度上是可以促进睡眠\n",
+      "那它一定程度上是可以促进睡眠的\n",
+      "1638/2707\n",
+      "1639/2707\n",
+      "1640/2707\n",
+      "1641/2707\n",
+      "1642/2707\n",
+      "Audio time = 4.7 sec.\n",
+      "Recognition time = 9.76432991027832 sec.\n",
+      "大家很多人是越数越兴奋\n",
+      "很多人是越数越兴奋\n",
+      "1643/2707\n",
+      "1644/2707\n",
+      "1645/2707\n",
+      "1646/2707\n",
+      "Audio time = 2.45 sec.\n",
+      "Recognition time = 8.565114974975586 sec.\n",
+      "或者说越数越焦虑\n",
+      "或者说越数越焦虑\n",
+      "1647/2707\n",
+      "1648/2707\n",
+      "1649/2707\n",
+      "1650/2707\n",
+      "Audio time = 2.5 sec.\n",
+      "Recognition time = 9.838749885559082 sec.\n",
+      "来其实会侵犯作用\n",
+      "其实会起反作用\n",
+      "1651/2707\n",
+      "1652/2707\n",
+      "1653/2707\n",
+      "1654/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 9.849634170532227 sec.\n",
+      "然后还有一种大家都应该有听说过的\n",
+      "还有一种大家应该都听说过的\n",
+      "1655/2707\n",
+      "1656/2707\n",
+      "1657/2707\n",
+      "1658/2707\n",
+      "Audio time = 3.72 sec.\n",
+      "Recognition time = 9.800726175308228 sec.\n",
+      "可以改善睡眠的方法就是安眠药\n",
+      "可以改善睡眠的方法就是安眠药\n",
+      "1659/2707\n",
+      "1660/2707\n",
+      "1661/2707\n",
+      "1662/2707\n",
+      "Audio time = 3.65 sec.\n",
+      "Recognition time = 9.522045135498047 sec.\n",
+      "安眠药确实是可以改善我们的睡眠\n",
+      "安眠药确实是可以改善我们的睡眠\n",
+      "1663/2707\n",
+      "1664/2707\n",
+      "1665/2707\n",
+      "1666/2707\n",
+      "Audio time = 3.58 sec.\n",
+      "Recognition time = 9.215401887893677 sec.\n",
+      "但是我在这里要提醒大家是\n",
+      "但是我在这里要提醒大家\n",
+      "1667/2707\n",
+      "1668/2707\n",
+      "1669/2707\n",
+      "1670/2707\n",
+      "Audio time = 5.15 sec.\n",
+      "Recognition time = 10.07035493850708 sec.\n",
+      "使用安眠药的时候一定要小型精神\n",
+      "使用安眠药的时候一定要小心谨慎\n",
+      "1671/2707\n",
+      "1672/2707\n",
+      "1673/2707\n",
+      "1674/2707\n",
+      "1675/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 9.595734119415283 sec.\n",
+      "因为常见的爱眠药都是作用于\n",
+      "因为常见的安眠药都是作用于\n",
+      "1676/2707\n",
+      "1677/2707\n",
+      "1678/2707\n",
+      "1679/2707\n",
+      "Audio time = 3.12 sec.\n",
+      "Recognition time = 9.69861388206482 sec.\n",
+      "与我们脑内的神经递质系统\n",
+      "我们脑内的神经递质系统\n",
+      "1680/2707\n",
+      "1681/2707\n",
+      "1682/2707\n",
+      "1683/2707\n",
+      "Audio time = 3.7 sec.\n",
+      "Recognition time = 10.467654943466187 sec.\n",
+      "然后这趟神经递质系统它却是调控睡眠\n",
+      "这套神经递质系统它确实调控睡眠\n",
+      "1684/2707\n",
+      "1685/2707\n",
+      "1686/2707\n",
+      "1687/2707\n",
+      "1688/2707\n",
+      "Audio time = 4.5 sec.\n",
+      "Recognition time = 11.265694856643677 sec.\n",
+      "但是他还负责执行我们闹的各种功能\n",
+      "但是它还负责执行我们脑的各种功能\n",
+      "1689/2707\n",
+      "1690/2707\n",
+      "1691/2707\n",
+      "1692/2707\n",
+      "Audio time = 4.15 sec.\n",
+      "Recognition time = 10.38594102859497 sec.\n",
+      "所以安眠药不仅会对你的睡眠产生影响\n",
+      "所以安眠药不仅会对你的睡眠产生影响\n",
+      "1693/2707\n",
+      "1694/2707\n",
+      "1695/2707\n",
+      "1696/2707\n",
+      "Audio time = 3.53 sec.\n",
+      "Recognition time = 10.750540018081665 sec.\n",
+      "他还会可能会影响我们的情绪\n",
+      "它可能还会影响我们的情绪\n",
+      "1697/2707\n",
+      "1698/2707\n",
+      "1699/2707\n",
+      "1700/2707\n",
+      "Audio time = 2.88 sec.\n",
+      "Recognition time = 10.43662428855896 sec.\n",
+      "认知功能包括学习基业\n",
+      "认知功能 包括学习记忆\n",
+      "1701/2707\n",
+      "1702/2707\n",
+      "1703/2707\n",
+      "1704/2707\n",
+      "Audio time = 3.45 sec.\n",
+      "Recognition time = 10.306946039199829 sec.\n",
+      "还有我甚至是运动功能等等\n",
+      "甚至是运动功能等等\n",
+      "1705/2707\n",
+      "1706/2707\n",
+      "1707/2707\n",
+      "1708/2707\n",
+      "Audio time = 3.92 sec.\n",
+      "Recognition time = 11.87840723991394 sec.\n",
+      "所以在使用来煤窑的时候一定要小型谨慎\n",
+      "所以在使用安眠药的时候一定要小心谨慎\n",
+      "1709/2707\n",
+      "1710/2707\n",
+      "1711/2707\n",
+      "1712/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 11.060353994369507 sec.\n",
+      "其实除了药物来改成睡眠还有一些\n",
+      "其实除了药物来改善睡眠\n",
+      "1713/2707\n",
+      "1714/2707\n",
+      "1715/2707\n",
+      "1716/2707\n",
+      "Audio time = 3.73 sec.\n",
+      "Recognition time = 11.671911001205444 sec.\n",
+      "认知行为疗法也可以改善睡眠\n",
+      "还有一些认知行为疗法也可以改善睡眠\n",
+      "1717/2707\n",
+      "1718/2707\n",
+      "1719/2707\n",
+      "1720/2707\n",
+      "Audio time = 7.25 sec.\n",
+      "Recognition time = 11.426790952682495 sec.\n",
+      "比如说把你的睡眠和卧室以及创建里一个关联\n",
+      "比如说把你的睡眠和卧室以及床建立一个关联\n",
+      "1721/2707\n",
+      "1722/2707\n",
+      "1723/2707\n",
+      "1724/2707\n",
+      "Audio time = 5.13 sec.\n",
+      "Recognition time = 11.306833028793335 sec.\n",
+      "在卧室里在床上就进行睡眠这个事情\n",
+      "在卧室里 在床上 就只进行睡眠这个事情\n",
+      "1725/2707\n",
+      "1726/2707\n",
+      "1727/2707\n",
+      "1728/2707\n",
+      "1729/2707\n",
+      "Audio time = 2.82 sec.\n",
+      "Recognition time = 10.859714031219482 sec.\n",
+      "就不在卧室和床上进行\n",
+      "就不要在卧室和床上进行\n",
+      "1730/2707\n",
+      "1731/2707\n",
+      "1732/2707\n",
+      "1733/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 11.359398126602173 sec.\n",
+      "如能比较好地建立这个关联的话\n",
+      "如果能比较好地建立这个关联的话\n",
+      "1734/2707\n",
+      "1735/2707\n",
+      "1736/2707\n",
+      "1737/2707\n",
+      "Audio time = 2.63 sec.\n",
+      "Recognition time = 10.975263118743896 sec.\n",
+      "花当你进入到这个环境里\n",
+      "当你进入到这个环境里\n",
+      "1738/2707\n",
+      "1739/2707\n",
+      "1740/2707\n",
+      "1741/2707\n",
+      "Audio time = 3.47 sec.\n",
+      "Recognition time = 12.985117197036743 sec.\n",
+      "就会能够比较容易睡着\n",
+      "就会能够比较容易睡着\n",
+      "1742/2707\n",
+      "1743/2707\n",
+      "1744/2707\n",
+      "1745/2707\n",
+      "Audio time = 2.32 sec.\n",
+      "Recognition time = 10.166368961334229 sec.\n",
+      "所有的科研问题\n",
+      "所有的科研问题\n",
+      "1746/2707\n",
+      "1747/2707\n",
+      "1748/2707\n",
+      "1749/2707\n",
+      "Audio time = 4.0 sec.\n",
+      "Recognition time = 11.109914064407349 sec.\n",
+      "我们不但有知其人我还要窒息所以然\n",
+      "我们不但要知其然我们还要知其所以然\n",
+      "1750/2707\n",
+      "1751/2707\n",
+      "1752/2707\n",
+      "1753/2707\n",
+      "Audio time = 6.48 sec.\n",
+      "Recognition time = 9.967283010482788 sec.\n",
+      "所以科学家们不带要研究睡眠如何产生的\n",
+      "所以科学家们不但要研究睡眠如何产生的\n",
+      "1754/2707\n",
+      "1755/2707\n",
+      "1756/2707\n",
+      "1757/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 10.022706985473633 sec.\n",
+      "他们还想研究我们为什么要睡觉\n",
+      "他们还想研究我们为什么要睡觉\n",
+      "1758/2707\n",
+      "1759/2707\n",
+      "1760/2707\n",
+      "1761/2707\n",
+      "Audio time = 2.55 sec.\n",
+      "Recognition time = 10.569955110549927 sec.\n",
+      "大家可能会觉得\n",
+      "大家可能会觉得\n",
+      "1762/2707\n",
+      "1763/2707\n",
+      "1764/2707\n",
+      "1765/2707\n",
+      "Audio time = 3.68 sec.\n",
+      "Recognition time = 11.552134275436401 sec.\n",
+      "我们为什么要睡觉这个问题还需要也中文\n",
+      "我们为什么要睡觉这个问题还需要研究吗\n",
+      "1766/2707\n",
+      "1767/2707\n",
+      "1768/2707\n",
+      "1769/2707\n",
+      "1770/2707\n",
+      "Audio time = 3.83 sec.\n",
+      "Recognition time = 9.068635940551758 sec.\n",
+      "但是我你仔细想想睡眠这个事情的话\n",
+      "但是如果你仔细想一想睡眠这个事情的话\n",
+      "1771/2707\n",
+      "1772/2707\n",
+      "1773/2707\n",
+      "1774/2707\n",
+      "Audio time = 2.9 sec.\n",
+      "Recognition time = 22.229652166366577 sec.\n",
+      "他其实也不是那么理所当然\n",
+      "它其实也不是那么理所当然\n",
+      "1775/2707\n",
+      "1776/2707\n",
+      "1777/2707\n",
+      "1778/2707\n",
+      "Audio time = 5.2 sec.\n",
+      "Recognition time = 10.066240072250366 sec.\n",
+      "因为未当动物进入到失眠的状态以后\n",
+      "因为当动物进入到睡眠的状态以后\n",
+      "1779/2707\n",
+      "1780/2707\n",
+      "1781/2707\n",
+      "1782/2707\n",
+      "Audio time = 3.5 sec.\n",
+      "Recognition time = 10.130698919296265 sec.\n",
+      "他是不能进食不能繁殖\n",
+      "它是不能进食 不能繁殖\n",
+      "1783/2707\n",
+      "1784/2707\n",
+      "1785/2707\n",
+      "1786/2707\n",
+      "Audio time = 2.93 sec.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognition time = 10.041284084320068 sec.\n",
+      "甚至是不能保护太子记得\n",
+      "甚至是不能保护它自己的\n",
+      "1787/2707\n",
+      "1788/2707\n",
+      "1789/2707\n",
+      "1790/2707\n",
+      "Audio time = 2.25 sec.\n",
+      "Recognition time = 9.727653980255127 sec.\n",
+      "但是基本是这辆的\n",
+      "但是即便是这样\n",
+      "1791/2707\n",
+      "1792/2707\n",
+      "1793/2707\n",
+      "1794/2707\n",
+      "Audio time = 2.48 sec.\n",
+      "Recognition time = 9.970431804656982 sec.\n",
+      "这两根我又睡了记忆点的叫了\n",
+      "动物也睡了几亿年的觉了\n",
+      "1795/2707\n",
+      "1796/2707\n",
+      "1797/2707\n",
+      "1798/2707\n",
+      "Audio time = 2.47 sec.\n",
+      "Recognition time = 10.636347770690918 sec.\n",
+      "这么说的话\n",
+      "这么说的话\n",
+      "1799/2707\n",
+      "1800/2707\n",
+      "1801/2707\n",
+      "1802/2707\n",
+      "Audio time = 3.15 sec.\n",
+      "Recognition time = 9.70245909690857 sec.\n",
+      "睡眠都不要付出那么大的代价\n",
+      "动物要付出那么大的代价\n",
+      "1803/2707\n",
+      "1804/2707\n",
+      "1805/2707\n",
+      "1806/2707\n",
+      "1807/2707\n",
+      "Audio time = 3.33 sec.\n",
+      "Recognition time = 10.953075170516968 sec.\n",
+      "所以睡眠应该是挺重要的\n",
+      "所以睡眠应该是挺重要的\n",
+      "1808/2707\n",
+      "1809/2707\n",
+      "1810/2707\n",
+      "1811/2707\n",
+      "Audio time = 2.55 sec.\n",
+      "Recognition time = 10.447063207626343 sec.\n",
+      "对于我们人类\n",
+      "对于我们人类\n",
+      "1812/2707\n",
+      "1813/2707\n",
+      "1814/2707\n",
+      "1815/2707\n",
+      "Audio time = 2.85 sec.\n",
+      "Recognition time = 10.32799506187439 sec.\n",
+      "如果一晚上的睡眠不足\n",
+      "如果一晚上的睡眠不足\n",
+      "1816/2707\n",
+      "1817/2707\n",
+      "1818/2707\n",
+      "1819/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.055874109268188 sec.\n",
+      "就会导致说认知功能在下降\n",
+      "就会导致认知功能的下降\n",
+      "1820/2707\n",
+      "1821/2707\n",
+      "1822/2707\n",
+      "1823/2707\n",
+      "Audio time = 2.8 sec.\n",
+      "Recognition time = 10.898871898651123 sec.\n",
+      "这个大家可能都有体会\n",
+      "这个大家可能都有体会\n",
+      "1824/2707\n",
+      "1825/2707\n",
+      "1826/2707\n",
+      "1827/2707\n",
+      "Audio time = 3.6 sec.\n",
+      "Recognition time = 11.943390130996704 sec.\n",
+      "一晚上没睡好第二天就感觉笨笨的\n",
+      "一晚上没睡好 第二天就感觉笨笨的\n",
+      "1828/2707\n",
+      "1829/2707\n",
+      "1830/2707\n",
+      "1831/2707\n",
+      "Audio time = 2.8 sec.\n",
+      "Recognition time = 10.328142881393433 sec.\n",
+      "然后如果长期学教的话\n",
+      "如果长期缺觉的话\n",
+      "1832/2707\n",
+      "1833/2707\n",
+      "1834/2707\n",
+      "1835/2707\n",
+      "Audio time = 4.03 sec.\n",
+      "Recognition time = 12.464287281036377 sec.\n",
+      "会增加你患多种疾病的风险包括\n",
+      "会增加罹患多种疾病的风险\n",
+      "1836/2707\n",
+      "1837/2707\n",
+      "1838/2707\n",
+      "1839/2707\n",
+      "Audio time = 5.73 sec.\n",
+      "Recognition time = 10.342688083648682 sec.\n",
+      "肥胖症糖尿病癌症精神疾病等等\n",
+      "包括肥胖症 糖尿病 癌症 精神疾病等等\n",
+      "1840/2707\n",
+      "1841/2707\n",
+      "1842/2707\n",
+      "1843/2707\n",
+      "Audio time = 4.2 sec.\n",
+      "Recognition time = 10.101732015609741 sec.\n",
+      "如果把大鼠放在向右边的图里面\n",
+      "如果把大鼠放在像右边的这个图里面\n",
+      "1844/2707\n",
+      "1845/2707\n",
+      "1846/2707\n",
+      "1847/2707\n",
+      "Audio time = 2.05 sec.\n",
+      "Recognition time = 10.227153778076172 sec.\n",
+      "里这样一个桩身里面\n",
+      "这样的一个装置里面\n",
+      "1848/2707\n",
+      "1849/2707\n",
+      "1850/2707\n",
+      "1851/2707\n",
+      "Audio time = 3.4 sec.\n",
+      "Recognition time = 9.403329133987427 sec.\n",
+      "对他进行持续的睡眠剥夺\n",
+      "对它进行持续的睡眠剥夺\n",
+      "1852/2707\n",
+      "1853/2707\n",
+      "1854/2707\n",
+      "1855/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.332170963287354 sec.\n",
+      "带来两周的世界大树就会死亡\n",
+      "大概两周的时间大鼠就会死亡\n",
+      "1856/2707\n",
+      "1857/2707\n",
+      "1858/2707\n",
+      "1859/2707\n",
+      "Audio time = 3.33 sec.\n",
+      "Recognition time = 8.910773992538452 sec.\n",
+      "但是为什么会这样我们还不太清楚\n",
+      "但是为什么会这样我们还不太清楚\n",
+      "1860/2707\n",
+      "1861/2707\n",
+      "1862/2707\n",
+      "1863/2707\n",
+      "Audio time = 4.7 sec.\n",
+      "Recognition time = 10.441707134246826 sec.\n",
+      "我前关于睡眠对脑的影响\n",
+      "目前关于睡眠对脑的影响\n",
+      "1864/2707\n",
+      "1865/2707\n",
+      "1866/2707\n",
+      "1867/2707\n",
+      "1868/2707\n",
+      "Audio time = 4.55 sec.\n",
+      "Recognition time = 10.263937950134277 sec.\n",
+      "睡眠可以在睡眠过程中我们脑内迁\n",
+      "在睡眠过程中我们脑内\n",
+      "1869/2707\n",
+      "1870/2707\n",
+      "1871/2707\n",
+      "1872/2707\n",
+      "Audio time = 3.65 sec.\n",
+      "Recognition time = 10.17685079574585 sec.\n",
+      "那前面讲的是警员会得到一些修复\n",
+      "前面讲的神经元 会得到一些修复\n",
+      "1873/2707\n",
+      "1874/2707\n",
+      "1875/2707\n",
+      "1876/2707\n",
+      "Audio time = 6.08 sec.\n",
+      "Recognition time = 10.446882009506226 sec.\n",
+      "这个是经人在我们脑内他会神经源直接会形成链结构\n",
+      "在脑内神经元之间会形成连接\n",
+      "1877/2707\n",
+      "1878/2707\n",
+      "1879/2707\n",
+      "1880/2707\n",
+      "Audio time = 2.17 sec.\n",
+      "Recognition time = 10.647816181182861 sec.\n",
+      "结构成一个这样的网络\n",
+      "构成一个这样的网络\n",
+      "1881/2707\n",
+      "1882/2707\n",
+      "1883/2707\n",
+      "1884/2707\n",
+      "Audio time = 2.8 sec.\n",
+      "Recognition time = 9.970585107803345 sec.\n",
+      "在我们醒着的时候\n",
+      "在我们醒着的时候\n",
+      "1885/2707\n",
+      "1886/2707\n",
+      "1887/2707\n",
+      "1888/2707\n",
+      "Audio time = 3.78 sec.\n",
+      "Recognition time = 10.700876235961914 sec.\n",
+      "因为脑接收后大量来自外界的星系\n",
+      "因为脑接收大量来自外界的信息\n",
+      "1889/2707\n",
+      "1890/2707\n",
+      "1891/2707\n",
+      "1892/2707\n",
+      "Audio time = 5.98 sec.\n",
+      "Recognition time = 11.620858192443848 sec.\n",
+      "所以这些事警员的需要接受处理传递这些星系\n",
+      "所以这些神经元需要接收处理传递这些信息\n",
+      "1893/2707\n",
+      "1894/2707\n",
+      "1895/2707\n",
+      "1896/2707\n",
+      "Audio time = 3.05 sec.\n",
+      "Recognition time = 10.85471796989441 sec.\n",
+      "在这个过程中他们会发生了一些性\n",
+      "在这个过程中它们会发生一些\n",
+      "1897/2707\n",
+      "1898/2707\n",
+      "1899/2707\n",
+      "1900/2707\n",
+      "Audio time = 2.62 sec.\n",
+      "Recognition time = 10.161369800567627 sec.\n",
+      "写形态和功能上的改变\n",
+      "形态和功能上的改变\n",
+      "1901/2707\n",
+      "1902/2707\n",
+      "1903/2707\n",
+      "1904/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 10.831066846847534 sec.\n",
+      "然后当我们寻中睡眠以后呢\n",
+      "当我们进入到睡眠以后\n",
+      "1905/2707\n",
+      "1906/2707\n",
+      "1907/2707\n",
+      "1908/2707\n",
+      "Audio time = 4.22 sec.\n",
+      "Recognition time = 10.85332202911377 sec.\n",
+      "这些形态和功能的改变可以得到一定的恢复\n",
+      "这些形态和功能的改变可以得到一定的恢复\n",
+      "1909/2707\n",
+      "1910/2707\n",
+      "1911/2707\n",
+      "1912/2707\n",
+      "Audio time = 2.98 sec.\n",
+      "Recognition time = 11.470728158950806 sec.\n",
+      "这样一遍又我们再次醒来的时候\n",
+      "这样以便于我们再次醒来的时候\n",
+      "1913/2707\n",
+      "1914/2707\n",
+      "1915/2707\n",
+      "1916/2707\n",
+      "Audio time = 4.53 sec.\n",
+      "Recognition time = 9.931190013885498 sec.\n",
+      "这些神经元可以更高效就觉得处理性\n",
+      "这些神经元可以更高效准确地\n",
+      "1917/2707\n",
+      "1918/2707\n",
+      "1919/2707\n",
+      "1920/2707\n",
+      "Audio time = 3.85 sec.\n",
+      "Recognition time = 10.750570058822632 sec.\n",
+      "处理新的星系传递性的星系\n",
+      "处理新的信息 传递新的信息\n",
+      "1921/2707\n",
+      "1922/2707\n",
+      "1923/2707\n",
+      "1924/2707\n",
+      "Audio time = 2.53 sec.\n",
+      "Recognition time = 10.854321241378784 sec.\n",
+      "但是因为我前面说了\n",
+      "但是因为我前面说了\n",
+      "1925/2707\n",
+      "1926/2707\n",
+      "1927/2707\n",
+      "1928/2707\n",
+      "Audio time = 3.37 sec.\n",
+      "Recognition time = 10.341864824295044 sec.\n",
+      "身边不足对我们的危害是防卫免得\n",
+      "睡眠不足对我们的危害是方方面面的\n",
+      "1929/2707\n",
+      "1930/2707\n",
+      "1931/2707\n",
+      "1932/2707\n",
+      "Audio time = 3.65 sec.\n",
+      "Recognition time = 10.24030590057373 sec.\n",
+      "所以水边的功能应该不止于此\n",
+      "所以睡眠的功能应该不止于此\n",
+      "1933/2707\n",
+      "1934/2707\n",
+      "1935/2707\n",
+      "1936/2707\n",
+      "Audio time = 4.43 sec.\n",
+      "Recognition time = 10.546146869659424 sec.\n",
+      "在升学与有一句广为流出来的话\n",
+      "在生物学领域有一句广为流传的话\n",
+      "1937/2707\n",
+      "1938/2707\n",
+      "1939/2707\n",
+      "1940/2707\n",
+      "1941/2707\n",
+      "Audio time = 2.75 sec.\n",
+      "Recognition time = 10.342514038085938 sec.\n",
+      "这句话原话是这样的\n",
+      "这句话原话是这样的\n",
+      "1942/2707\n",
+      "1943/2707\n",
+      "1944/2707\n",
+      "1945/2707\n",
+      "Audio time = 4.57 sec.\n",
+      "Recognition time = 9.031803846359253 sec.\n",
+      "那绯羽白熬了去梅瓶来都比我懂事\n",
+      "Nothing in biology makes sense except in light of evolution\n",
+      "1946/2707\n",
+      "1947/2707\n",
+      "1948/2707\n",
+      "1949/2707\n",
+      "Audio time = 3.82 sec.\n",
+      "Recognition time = 9.731159210205078 sec.\n",
+      "大意就是说任何生物学的问题到\n",
+      "大意就是说任何生物学的问题\n",
+      "1950/2707\n",
+      "1951/2707\n",
+      "1952/2707\n",
+      "1953/2707\n",
+      "Audio time = 4.05 sec.\n",
+      "Recognition time = 10.21561884880066 sec.\n",
+      "都要从演化的交通去分析才有意义\n",
+      "都要从演化的角度去分析才有意义\n",
+      "1954/2707\n",
+      "1955/2707\n",
+      "1956/2707\n",
+      "1957/2707\n",
+      "Audio time = 3.34 sec.\n",
+      "Recognition time = 12.388890743255615 sec.\n",
+      "如果从演化了角度我们想一想\n",
+      "如果从演化的角度我们想一想\n",
+      "1958/2707\n",
+      "1959/2707\n",
+      "1960/2707\n",
+      "1961/2707\n",
+      "Audio time = 1.98 sec.\n",
+      "Recognition time = 9.58765721321106 sec.\n",
+      "为什么要睡觉\n",
+      "为什么要睡觉\n",
+      "1962/2707\n",
+      "1963/2707\n",
+      "1964/2707\n",
+      "1965/2707\n",
+      "Audio time = 3.3 sec.\n",
+      "Recognition time = 10.277790307998657 sec.\n",
+      "为什么地球上东问你睡了几亿年了\n",
+      "为什么地球上的动物已经睡了几亿年了\n",
+      "1966/2707\n",
+      "1967/2707\n",
+      "1968/2707\n",
+      "1969/2707\n",
+      "Audio time = 3.2 sec.\n",
+      "Recognition time = 11.172950983047485 sec.\n",
+      "就如果从这个叫伦分析的话我\n",
+      "如果从这个角度来分析的话\n",
+      "1970/2707\n",
+      "1971/2707\n",
+      "1972/2707\n",
+      "1973/2707\n",
+      "Audio time = 3.42 sec.\n",
+      "Recognition time = 9.000153303146362 sec.\n",
+      "我们可能会得到一些新的提示\n",
+      "我们可能会得到一些新的提示\n",
+      "1974/2707\n",
+      "1975/2707\n",
+      "1976/2707\n",
+      "1977/2707\n",
+      "Audio time = 4.95 sec.\n",
+      "Recognition time = 10.396843671798706 sec.\n",
+      "虽然涤纶尚东都大多数中午都需要睡觉\n",
+      "虽然地球上大多数动物都需要睡觉\n",
+      "1978/2707\n",
+      "1979/2707\n",
+      "1980/2707\n",
+      "1981/2707\n",
+      "Audio time = 3.05 sec.\n",
+      "Recognition time = 8.751291990280151 sec.\n",
+      "他们的睡眠其实还挺不一样的\n",
+      "它们的睡眠其实还挺不一样的\n",
+      "1982/2707\n",
+      "1983/2707\n",
+      "1984/2707\n",
+      "1985/2707\n",
+      "Audio time = 4.6 sec.\n",
+      "Recognition time = 8.490720987319946 sec.\n",
+      "比如说一种叫做野猴的动物\n",
+      "比如说一种叫做夜猴的动物\n",
+      "1986/2707\n",
+      "1987/2707\n",
+      "1988/2707\n",
+      "1989/2707\n",
+      "Audio time = 2.58 sec.\n",
+      "Recognition time = 8.635629177093506 sec.\n",
+      "他就需要睡的比较久\n",
+      "它就需要睡得比较久\n",
+      "1990/2707\n",
+      "1991/2707\n",
+      "1992/2707\n",
+      "1993/2707\n",
+      "Audio time = 3.45 sec.\n",
+      "Recognition time = 10.498374938964844 sec.\n",
+      "他每天可能要睡大约十七个小时\n",
+      "它每天可能要睡大约17个小时\n",
+      "1994/2707\n",
+      "1995/2707\n",
+      "1996/2707\n",
+      "1997/2707\n",
+      "Audio time = 4.1 sec.\n",
+      "Recognition time = 11.285339117050171 sec.\n",
+      "你的出五毛该来每天睡十二个半小时\n",
+      "你的宠物猫大概每天睡12个半小时\n",
+      "1998/2707\n",
+      "1999/2707\n",
+      "2000/2707\n",
+      "2001/2707\n",
+      "Audio time = 4.45 sec.\n",
+      "Recognition time = 10.137523889541626 sec.\n",
+      "我们人类的一般是需要八个小时所有的睡眠\n",
+      "我们人类一般需要8个小时左右的睡眠\n",
+      "2002/2707\n",
+      "2003/2707\n",
+      "2004/2707\n",
+      "2005/2707\n",
+      "Audio time = 2.87 sec.\n",
+      "Recognition time = 10.034235954284668 sec.\n",
+      "而有一些动物就睡的比较少比如\n",
+      "而有一些动物就睡得比较少\n",
+      "2006/2707\n",
+      "2007/2707\n",
+      "2008/2707\n",
+      "2009/2707\n",
+      "Audio time = 3.63 sec.\n",
+      "Recognition time = 9.728991985321045 sec.\n",
+      "比如说山羊和马\n",
+      "比如说山羊和马\n",
+      "2010/2707\n",
+      "2011/2707\n",
+      "2012/2707\n",
+      "2013/2707\n",
+      "2014/2707\n",
+      "Audio time = 3.32 sec.\n",
+      "Recognition time = 10.138468980789185 sec.\n",
+      "到这里大家可能会很好奇不\n",
+      "到这里大家可能会很好奇\n",
+      "2015/2707\n",
+      "2016/2707\n",
+      "2017/2707\n",
+      "2018/2707\n",
+      "Audio time = 3.18 sec.\n",
+      "Recognition time = 10.477406978607178 sec.\n",
+      "或不还有动物睡得更少\n",
+      "会不会还有动物睡得更少\n",
+      "2019/2707\n",
+      "2020/2707\n",
+      "2021/2707\n",
+      "2022/2707\n",
+      "Audio time = 2.58 sec.\n",
+      "Recognition time = 11.842370986938477 sec.\n",
+      "甚至是不用睡觉的\n",
+      "甚至是不用睡觉呢\n",
+      "2023/2707\n",
+      "2024/2707\n",
+      "2025/2707\n",
+      "2026/2707\n",
+      "Audio time = 3.25 sec.\n",
+      "Recognition time = 8.909492015838623 sec.\n",
+      "也是可能有这样的动物的\n",
+      "也是可能有这样的动物的\n",
+      "2027/2707\n",
+      "2028/2707\n",
+      "2029/2707\n",
+      "2030/2707\n",
+      "Audio time = 5.08 sec.\n"
+     ]
+    }
+   ],
+   "source": [
+    "subtitles = []\n",
+    "new_subtitles = []\n",
+    "srtfile = \"data/yixi_original.srt\"\n",
+    "srtfile_recognized = \"data/yixi.srt\"\n",
+    "wavfile = \"data/yixi.wav\"\n",
+    "\n",
+    "rate, data = read_wav(wavfile)\n",
+    "\n",
+    "with open(srtfile, 'r') as f:\n",
+    "    for line in f:\n",
+    "        subtitles.append(line.strip())\n",
+    "\n",
+    "j = 0\n",
+    "for i in range(len(subtitles)):\n",
+    "    print(str(i)+\"/\"+str(len(subtitles)))\n",
+    "    if \"-->\" in subtitles[i]:\n",
+    "        time1, time2 = [timeStamp2Num(x, rate) for x in subtitles[i].split(\" --> \")]\n",
+    "        time1 = max([0, time1-8000])\n",
+    "        time2 = time2+8000\n",
+    "        print(\"Audio time = \"+str((time2-time1)/16000.0)+\" sec.\")\n",
+    "        \n",
+    "        recog_starting_time = time.time()\n",
+    "        currentdata = data[time1:time2]\n",
+    "        if len(currentdata)<100:\n",
+    "            continue\n",
+    "        currentdata = mergeChannels(currentdata)\n",
+    "        if len(currentdata)>160240:\n",
+    "            j+=1\n",
+    "            new_subtitles.append(str(j))\n",
+    "            new_subtitles.append(subtitles[i])\n",
+    "            new_subtitles.append(\"语句太长，识别失败\")\n",
+    "            new_subtitles.append(\"\")\n",
+    "            continue\n",
+    "        currentdata = zero_padding_1d(currentdata, 160240)\n",
+    "        a_seg = AudioSegment(currentdata, rate)\n",
+    "        xs = np.transpose(np.array([af.featurize(a_seg)]), [0,2,1])\n",
+    "        \n",
+    "        pred = model.predict(sess, xs)[0]\n",
+    "        pred_dense = sparseTuples2dense(pred)\n",
+    "        detected_line = []\n",
+    "        for stuff in pred_dense[0]:\n",
+    "            if stuff!=-1:\n",
+    "                detected_line.append(stuff)\n",
+    "        if len(detected_line)<1:\n",
+    "            continue\n",
+    "        pinyin = pyParser.decodeIndices(detected_line, useUnderline = False)\n",
+    "        response = urlopen(\"https://www.google.com/inputtools/request?ime=pinyin&ie=utf-8&oe=utf-8&app=translate&num=10&text=\"+pinyin)\n",
+    "        html = response.read()\n",
+    "        result = (html.decode('utf8')).split(\",\")[2][2:-1]\n",
+    "        \n",
+    "        print(\"Recognition time = \"+str(time.time()-recog_starting_time)+\" sec.\")\n",
+    "        print(result)\n",
+    "        print(subtitles[i+1])\n",
+    "        \n",
+    "        j+=1\n",
+    "        new_subtitles.append(str(j))\n",
+    "        new_subtitles.append(subtitles[i])\n",
+    "        new_subtitles.append(result)\n",
+    "        new_subtitles.append(\"\")\n",
+    "\n",
+    "new_subtitles = new_subtitles[:-1]\n",
+    "with open(srtfile_recognized, 'w+') as f:\n",
+    "    for line in new_subtitles:\n",
+    "        f.write(line+\"\\n\")\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 去掉空格，改数字，英文，和“他，她，它”\n",
+    "subtitles = []\n",
+    "new_subtitles = []\n",
+    "srtfile = \"data/zongli_original.srt\"\n",
+    "srtfile_recognized = \"data/zongli.srt\"\n",
+    "wavfile = \"data/zongli.wav\"\n",
+    "\n",
+    "rate, data = read_wav(wavfile)\n",
+    "\n",
+    "with open(srtfile, 'r') as f:\n",
+    "    for line in f:\n",
+    "        subtitles.append(line.strip())\n",
+    "\n",
+    "j = 0\n",
+    "for i in range(len(subtitles))):\n",
+    "    print(str(i)+\"/\"+str(len(subtitles)))\n",
+    "    if \"-->\" in subtitles[i]:\n",
+    "        time1, time2 = [timeStamp2Num(x, rate) for x in subtitles[i].split(\" --> \")]\n",
+    "        time1 = max([0, time1-8000])\n",
+    "        time2 = time2+8000\n",
+    "        \n",
+    "        currentdata = data[time1:time2]\n",
+    "        if len(currentdata)<100:\n",
+    "            continue\n",
+    "        currentdata = mergeChannels(currentdata)\n",
+    "        if len(currentdata)>160240:\n",
+    "            j+=1\n",
+    "            new_subtitles.append(str(j))\n",
+    "            new_subtitles.append(subtitles[i])\n",
+    "            new_subtitles.append(subtitles[i+1])\n",
+    "            new_subtitles.append(\"\")\n",
+    "            continue\n",
+    "        currentdata = zero_padding_1d(currentdata, 160240)\n",
+    "        a_seg = AudioSegment(currentdata, rate)\n",
+    "        xs = np.transpose(np.array([af.featurize(a_seg)]), [0,2,1])\n",
+    "        \n",
+    "        pred = model.predict(sess, xs)[0]\n",
+    "        pred_dense = sparseTuples2dense(pred)\n",
+    "        detected_line = []\n",
+    "        for stuff in pred_dense[0]:\n",
+    "            if stuff!=-1:\n",
+    "                detected_line.append(stuff)\n",
+    "        if len(detected_line)<1:\n",
+    "            continue\n",
+    "        pinyin = pyParser.decodeIndices(detected_line, useUnderline = False)\n",
+    "        response = urlopen(\"https://www.google.com/inputtools/request?ime=pinyin&ie=utf-8&oe=utf-8&app=translate&num=10&text=\"+pinyin)\n",
+    "        html = response.read()\n",
+    "        result = (html.decode('utf8')).split(\",\")[2][2:-1]\n",
+    "        \n",
+    "        print(result)\n",
+    "        print(subtitles[i+1])\n",
+    "        \n",
+    "        j+=1\n",
+    "        new_subtitles.append(str(j))\n",
+    "        new_subtitles.append(subtitles[i])\n",
+    "        new_subtitles.append(result)\n",
+    "        new_subtitles.append(\"\")\n",
+    "\n",
+    "new_subtitles = new_subtitles[:-1]\n",
+    "with open(srtfile_recognized, 'w+') as f:\n",
+    "    for line in new_subtitles:\n",
+    "        f.write(line+\"\\n\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/subtitle_demo.py b/subtitle_demo.py
new file mode 100644
index 0000000..9a800bf
--- /dev/null
+++ b/subtitle_demo.py
@@ -0,0 +1,57 @@
+import os
+import time
+import warnings
+warnings.filterwarnings("ignore", message="numpy.dtype size changed")
+warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    import tensorflow as tf
+import numpy as np
+from urllib.request import urlopen
+
+from lib.tools_batch import *
+from lib.tools_math import *
+from lib.tools_sparse import *
+from lib.contrib.audio_featurizer import AudioFeaturizer
+from lib.contrib.audio import AudioSegment
+from model901 import *
+model_name = "v901"
+
+def timeStamp2Num(timeStamp, rate):
+    """
+    timeStamp str: 00:00:01,879
+    rate int: the sampling rate
+    return int
+    """
+    secs, millisec = timeStamp.split(",")
+    hour, minute, sec = secs.split(":")
+    millisec = float(millisec)*0.001
+    sec = float(hour)*3600+float(minute)*60+float(sec)
+    num = int(rate*(sec+millisec))
+    return num
+
+pyParser = pinyinParser("lib/pinyinDictNoTone.pickle")
+model = model(409)
+af = AudioFeaturizer()
+
+with tf.Session() as sess:
+    saver = tf.train.Saver()
+    saver.restore(sess, "models/"+model_name+"/"+model_name+"_0.ckpt")
+
+    rate, data = read_wav("data/test.wav")
+    data = mergeChannels(data)
+    data = zero_padding_1d(data, 160240)
+    a_seg = AudioSegment(data, rate)
+    xs = np.transpose(np.array([af.featurize(a_seg)]), [0,2,1])
+
+    pred = model.predict(sess, xs)[0]
+    pred_dense = sparseTuples2dense(pred)
+    detected_line = []
+    for stuff in pred_dense[0]:
+        if stuff!=-1:
+            detected_line.append(stuff)
+    pinyin = pyParser.decodeIndices(detected_line, useUnderline = False)
+    print(pinyin)
+    response = urlopen("https://www.google.com/inputtools/request?ime=pinyin&ie=utf-8&oe=utf-8&app=translate&num=10&text="+pinyin)
+    html = response.read()
+    result = html.split(",")[2][2:-1]
diff --git a/test_audio.wav b/test_audio.wav
new file mode 100644
index 0000000..97caa74
Binary files /dev/null and b/test_audio.wav differ
diff --git a/test_audio2.wav b/test_audio2.wav
new file mode 100644
index 0000000..eea82aa
Binary files /dev/null and b/test_audio2.wav differ
diff --git a/train901.py b/train901.py
new file mode 100644
index 0000000..1266e0b
--- /dev/null
+++ b/train901.py
@@ -0,0 +1,74 @@
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = input("Which GPU? ")
+import time
+import warnings
+warnings.filterwarnings("ignore", message="numpy.dtype size changed")
+warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    import tensorflow as tf
+import numpy as np
+
+from lib.tools_batch import *
+from lib.tools_math import *
+from model901 import *
+
+def get_learningRate(step):
+    # return max(4e-4*(0.99999**step), 2e-5)
+    return 2e-4
+
+TEST_ROUND = 1
+BATCH_SIZE = 128
+TEST_SIZE = 16
+AUGMENTATION = True
+NUM_STEP = int(1e7)
+
+model_name = "v901"
+saving_period = 200
+num_labels = 407
+num_class = 409
+bg = BatchGetter("../data/data_aishell/wav", "../data/data_aishell/transcript/aishell_transcript_v0.8.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+bg2 = BatchGetter("../data/youtube_subtitles/wav", "../data/youtube_subtitles/subs.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+pyParser = pinyinParser("lib/pinyinDictNoTone.pickle")
+model = model(num_class)
+if model_name not in os.listdir('models/'):
+    os.mkdir('models/'+model_name)
+
+gpu_options = tf.GPUOptions(allow_growth=True)
+with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,allow_soft_placement=True,log_device_placement=False)) as sess:
+
+    sess.run(tf.global_variables_initializer())
+    saver = tf.train.Saver()
+    # tensorboard --logdir logs/
+    summary_writer = tf.summary.FileWriter(logdir = "logs", graph = tf.get_default_graph())
+    saver.restore(sess, "models/"+model_name+"/"+model_name+"_0.ckpt")
+
+    for i in range(1, NUM_STEP+1):
+
+        lr = get_learningRate(i)
+        if i%2==0:
+            xs, ys = bg.get_batch(BATCH_SIZE, batch_type = 'train')
+        else:
+            xs, ys = bg2.get_batch(BATCH_SIZE, batch_type = 'train')
+        loss, summary = model.train(sess, lr, xs, ys)
+        summary_writer.add_summary(summary, i)
+        print(i, loss)
+
+        if i%saving_period == 0:
+            print("Learning rate =", lr)
+            save_path = saver.save(sess, "models/"+model_name+"/"+model_name+"_"+str(int(i/50000))+".ckpt")
+            print("Model saved in path: "+save_path)
+
+            ave_loss = 0.0
+            for i in range(2):
+                if i==0:
+                    xs, ys = bg.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                else:
+                    xs, ys = bg2.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                loss = model.get_loss(sess, xs, ys)
+                pred = model.predict(sess, xs)[0]
+                report_accuracy(pred, ys, pyParser)
+                ave_loss+=loss
+            print("Test Loss = "+str(ave_loss/float(TEST_ROUND)))
diff --git a/train902.py b/train902.py
new file mode 100644
index 0000000..68dfb37
--- /dev/null
+++ b/train902.py
@@ -0,0 +1,74 @@
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = input("Which GPU? ")
+import time
+import warnings
+warnings.filterwarnings("ignore", message="numpy.dtype size changed")
+warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    import tensorflow as tf
+import numpy as np
+
+from lib.tools_batch import *
+from lib.tools_math import *
+from model902 import *
+
+def get_learningRate(step):
+    # return max(4e-4*(0.99999**step), 2e-5)
+    return 2e-4
+
+TEST_ROUND = 1
+BATCH_SIZE = 64
+TEST_SIZE = 16
+AUGMENTATION = True
+NUM_STEP = int(1e7)
+
+model_name = "v902"
+saving_period = 200
+num_labels = 407
+num_class = 409
+bg = BatchGetter("../data/data_aishell/wav", "../data/data_aishell/transcript/aishell_transcript_v0.8.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+bg2 = BatchGetter("../data/youtube_subtitles/wav", "../data/youtube_subtitles/subs.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+pyParser = pinyinParser("lib/pinyinDictNoTone.pickle")
+model = model(num_class)
+if model_name not in os.listdir('models/'):
+    os.mkdir('models/'+model_name)
+
+gpu_options = tf.GPUOptions(allow_growth=True)
+with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,allow_soft_placement=True,log_device_placement=False)) as sess:
+
+    sess.run(tf.global_variables_initializer())
+    saver = tf.train.Saver()
+    # tensorboard --logdir logs/
+    summary_writer = tf.summary.FileWriter(logdir = "logs", graph = tf.get_default_graph())
+    saver.restore(sess, "models/"+model_name+"/"+model_name+"_0.ckpt")
+
+    for i in range(1, NUM_STEP+1):
+
+        lr = get_learningRate(i)
+        if i%2==0:
+            xs, ys = bg.get_batch(BATCH_SIZE, batch_type = 'train')
+        else:
+            xs, ys = bg2.get_batch(BATCH_SIZE, batch_type = 'train')
+        loss, summary = model.train(sess, lr, xs, ys)
+        summary_writer.add_summary(summary, i)
+        print(i, loss)
+
+        if i%saving_period == 0:
+            print("Learning rate =", lr)
+            save_path = saver.save(sess, "models/"+model_name+"/"+model_name+"_"+str(int(i/50000))+".ckpt")
+            print("Model saved in path: "+save_path)
+
+            ave_loss = 0.0
+            for i in range(2):
+                if i==0:
+                    xs, ys = bg.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                else:
+                    xs, ys = bg2.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                loss = model.get_loss(sess, xs, ys)
+                pred = model.predict(sess, xs)[0]
+                report_accuracy(pred, ys, pyParser)
+                ave_loss+=loss
+            print("Test Loss = "+str(ave_loss/float(TEST_ROUND)))
diff --git a/train903.py b/train903.py
new file mode 100644
index 0000000..cf46f1a
--- /dev/null
+++ b/train903.py
@@ -0,0 +1,74 @@
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = input("Which GPU? ")
+import time
+import warnings
+warnings.filterwarnings("ignore", message="numpy.dtype size changed")
+warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    import tensorflow as tf
+import numpy as np
+
+from lib.tools_batch import *
+from lib.tools_math import *
+from model903 import *
+
+def get_learningRate(step):
+    # return max(4e-4*(0.99999**step), 2e-5)
+    return 2e-4
+
+TEST_ROUND = 1
+BATCH_SIZE = 32
+TEST_SIZE = 16
+AUGMENTATION = True
+NUM_STEP = int(1e7)
+
+model_name = "v903"
+saving_period = 200
+num_labels = 407
+num_class = 409
+bg = BatchGetter("../data/data_aishell/wav", "../data/data_aishell/transcript/aishell_transcript_v0.8.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+bg2 = BatchGetter("../data/youtube_subtitles/wav", "../data/youtube_subtitles/subs.txt",
+                    "lib/pinyinDictNoTone.pickle", "../data/backgrounds/", server = True)
+pyParser = pinyinParser("lib/pinyinDictNoTone.pickle")
+model = model(num_class)
+if model_name not in os.listdir('models/'):
+    os.mkdir('models/'+model_name)
+
+gpu_options = tf.GPUOptions(allow_growth=True)
+with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,allow_soft_placement=True,log_device_placement=False)) as sess:
+
+    sess.run(tf.global_variables_initializer())
+    saver = tf.train.Saver()
+    # tensorboard --logdir logs/
+    summary_writer = tf.summary.FileWriter(logdir = "logs", graph = tf.get_default_graph())
+    saver.restore(sess, "models/"+model_name+"/"+model_name+"_0.ckpt")
+
+    for i in range(1, NUM_STEP+1):
+
+        lr = get_learningRate(i)
+        if i%2==0:
+            xs, ys = bg.get_batch(BATCH_SIZE, batch_type = 'train')
+        else:
+            xs, ys = bg2.get_batch(BATCH_SIZE, batch_type = 'train')
+        loss, summary = model.train(sess, lr, xs, ys)
+        summary_writer.add_summary(summary, i)
+        print(i, loss)
+
+        if i%saving_period == 0:
+            print("Learning rate =", lr)
+            save_path = saver.save(sess, "models/"+model_name+"/"+model_name+"_"+str(int(i/50000))+".ckpt")
+            print("Model saved in path: "+save_path)
+
+            ave_loss = 0.0
+            for i in range(2):
+                if i==0:
+                    xs, ys = bg.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                else:
+                    xs, ys = bg2.get_batch(TEST_SIZE, batch_type = 'test', augmentation = False)
+                loss = model.get_loss(sess, xs, ys)
+                pred = model.predict(sess, xs)[0]
+                report_accuracy(pred, ys, pyParser)
+                ave_loss+=loss
+            print("Test Loss = "+str(ave_loss/float(TEST_ROUND)))