CV+publications

Author: tang-kevin

Files/CV/Tang_Kevin_CV.pdf

@@ -7,7 +7,7 @@ @InProceedings{JeongSchmitzKakoluRSteinTang_LDL_SIGMORPHON_2023
   publisher = {Association for Computational Linguistics},
   month     = {July},
   pages     = {138--150},
-  url       = {https://aclanthology.org/2023.sigmorphon-1.16},
+  doi       = {10.18653/v1/2023.sigmorphon-1.16},
   abstract  = {This paper presents our submission to the SIGMORPHON 2023 task 2 of Cognitively Plausible Morphophonological Generalization in Korean. We implemented both Linear Discriminative Learning and Transformer models and found that the Linear Discriminative Learning model trained on a combination of corpus and experimental data showed the best performance with the overall accuracy of around 83\%. We found that the best model must be trained on both corpus data and the experimental data of one particular participant. Our examination of speaker-variability and speaker-specific information did not explain why a particular participant combined well with the corpus data. We recommend Linear Discriminative Learning models as a future non-neural baseline system, owning to its training speed, accuracy, model interpretability and cognitive plausibility. In order to improve the model performance, we suggest using bigger data and/or performing data augmentation and incorporating speaker- and item-specifics considerably.},
   address   = {Toronto, Canada},
 }

Files/publications/JeongSchmitzKRamarao_et_al_SIGMORPHON2023.bib

@@ -14,7 +14,7 @@ @inproceedings{porwal-etal-2025-analysis
     year = "2025",
     address = "Albuquerque, New Mexico",
     publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.findings-naacl.431/",
+    doi       = "10.18653/v1/2025.findings-naacl.431",
     pages = "7744--7756",
     ISBN = "979-8-89176-195-7"
 }

Files/publications/PorwalRozetGowdaHouckTangMoeller_2025_LLMAAE_FindingsNAACL.bib

@@ -0,0 +1,12 @@
+@article{WaylandMeyerVellozziTang_2025_Individualdifferences_speechcomm,
+title = {Individual differences in language acquisition: The impact of study abroad on native {E}nglish speakers learning {S}panish},
+journal = {Speech Communication},
+volume = {174},
+pages = {103301},
+year = {2025},
+issn = {0167-6393},
+doi = {10.1016/j.specom.2025.103301},
+author = {Ratree Wayland and Rachel Meyer and Sophia Vellozzi and Kevin Tang},
+keywords = {Spanish stops, Lenition, Study abroad, Deep neural network},
+abstract = {This study investigated the acquisition of lenition in Spanish voiced stops (/b, d, ɡ/) by native English speakers during a study-abroad program, focusing on individual differences and influencing factors. Lenition, characterized by the weakening of stops into fricative-like ([β], [ð], [ɣ]) or approximant-like ([β̞], [ð̞], [ɣ̞]) forms, poses challenges for L2 learners due to its gradient nature and the absence of analogous approximant forms in English. Results indicated that learners aligned with native speakers in recognizing voicing as the primary cue for lenition, yet their productions diverged, favoring fricative-like over approximant-like realizations. This preference reflects the combined influence of articulatory ease, acoustic salience, and cognitive demands. Individual variability in learners’ trajectories highlights the role of exposure to native input and sociolinguistic engagement. Learners benefitting from richer, informal interactions with native speakers showed greater alignment with native patterns, while others demonstrated more limited progress. However, native input alone was insufficient for learners to internalize subtler distinctions such as place of articulation and stress. These findings emphasize the need for combining immersive experiences with targeted instructional strategies to address articulatory and cognitive challenges. This study contributes to the understanding of L2 phonological acquisition and offers insights for designing more effective language learning programs to support lenition acquisition in Spanish.}
+}