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Installation & Setup Guide

For comprehensive setup details, see the published journal article.

Quick Start

Requirements

  • Python 3.8+
  • 4GB RAM (8GB for training)
  • Optional: NVIDIA GPU

Installation

# Clone and setup
git clone https://github.com/yourusername/7-Emotion-Bangla-Speech-Recognition-Model.git
cd 7-Emotion-Bangla-Speech-Recognition-Model

# Create environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install backend dependencies
cd emotion-detection/backend
pip install -r requirements.txt

# Install frontend dependencies
cd ../
npm install

Verify Installation

python -c "import torch; print(torch.__version__)"
python -c "import librosa; print(librosa.__version__)"

Running the Application

Web Application

# Terminal 1: Backend
cd emotion-detection/backend
python app.py

# Terminal 2: Frontend  
cd emotion-detection
npm start

Open: http://localhost:3000

Raspberry Pi Deployment

ssh pi@raspberrypi.local
git clone <repo-url>
cd emotion-detection-raspi/backend
pip install -r requirements-pi.txt
python app.py

Model Usage Example

import torch
from backend.model import load_model, extract_features, predict_emotion

# Load pre-trained model (path relative to backend/)
model = load_model('Final_MultiScale_Realtime_Model.pth')

# Extract MFCC features from a 3-second 16kHz WAV file
features = extract_features('audio.wav')

# Predict emotion label
emotion = predict_emotion(model, features)
print("Predicted emotion:", emotion)

See: Final CNN + BiLSTM.ipynb

Troubleshooting

Issue Solution
PyTorch import error pip install torch --index-url https://download.pytorch.org/whl/cpu
CUDA not found Use CPU mode or update GPU drivers
Port 5000 in use FLASK_PORT=5001 python app.py
ffmpeg missing apt-get install ffmpeg (Linux) or brew install ffmpeg (macOS)
Raspberry Pi slow Reduce batch size or enable quantization

For Details

📖 Full Journal Article - Complete methodology
📚 ARCHITECTURE.md - System design
🏗️ RESEARCH.md - Research details
💻 Final Model Notebook - Full implementation

Last Updated: February 2026