Papers by Kalvin Chang
WikiHan: A New Comparative Dataset for Chinese Languages (2022.coling-1)
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| Challenge: | Currently, there are 1.3 billion speakers of Sinitic varieties, making the family one of the largest in terms of speaker count. |
| Approach: | They have collected a single constituent and structured form of Chinese varieties for comparative linguistics and Chinese NLP. |
| Outcome: | The proposed dataset contains 67,943 entries across 8 varieties and Middle Chinese . it achieves 54.11% accuracy and 17.69% error rate on a protoform reconstruction task . |
POWSM: A Phonetic Open Whisper-Style Speech Foundation Model (2026.acl-long)
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Chin-Jou Li, Kalvin Chang, Shikhar Bharadwaj, Eunjung Yeo, Kwanghee Choi, Jian Zhu, David R. Mortensen, Shinji Watanabe
| Challenge: | Phone-level modeling of speech is a common approach to speech recognition, but it relies on task-specific architectures and datasets. |
| Approach: | They propose a phonetic framework capable of performing multiple phone-related tasks . they propose 'Phonetic Open Whisper-style Speech Model' that can perform these tasks together . |
| Outcome: | The proposed model outperforms or matches specialized PR models of similar size while supporting G2P, P2G, and ASR. |
Linear Script Representations in Speech Foundation Models Enable Zero-Shot Transliteration (2026.findings-acl)
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Ryan Soh-Eun Shim, Kwanghee Choi, Kalvin Chang, Ming-Hao Hsu, Florian Eichin, Zhizheng Wu, Alane Suhr, Michael A. Hedderich, David Harwath, David R. Mortensen, Barbara Plank
| Challenge: | We show that script information is linearly encoded in the activation space of multilingual speech models . modifying activations at inference time induces script change even in unconventional pairings . |
| Approach: | They propose to add script vectors to activations at test time to induce script change . they also show that script information is linearly encoded in the activation space of multilingual speech models . |
| Outcome: | The proposed approach can induce script change even in unconventional language-script pairings. |
Programming by Example meets Historical Linguistics: A Large Language Model Based Approach to Sound Law Induction (2025.acl-long)
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Atharva Naik, Darsh Agrawal, Hong Sng, Clayton Marr, Kexun Zhang, Nathaniel Romney Robinson, Kalvin Chang, Rebecca Byrnes, Aravind Mysore, Carolyn Rose, David R. Mortensen
| Challenge: | Historical linguists have written programs that convert reconstructed words into their attested descendants via ordered string rewrite functions. |
| Approach: | They propose to use a model to generate a "similar distribution" for sound law induction . they propose four kinds of methods with varying amounts of inductive bias to investigate best performance . |
| Outcome: | The proposed model shows that it can be fine tuned with training data and evaluation data. |
Phonotactic Complexity across Dialects (2024.lrec-main)
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| Challenge: | Recent studies show a moderate negative correlation between phonotactic complexity and word length in 106 languages. |
| Approach: | They propose to use a phone-level language model to measure phonotactic complexity . they find a tradeoff between word length and phonomactic complex . |
| Outcome: | The proposed model shows that low phonotactic complexity dialects concentrate around capital regions. |
PRiSM: Benchmarking Phone Realization in Speech Models (2026.acl-long)
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Shikhar Bharadwaj, Chin-Jou Li, Yoonjae Kim, Kwanghee Choi, Eunjung Yeo, Ryan Soh-Eun Shim, Hanyu Zhou, Brendon Boldt, Karen Rosero, Kalvin Chang, Darsh Agrawal, Keer Xu, Chao-Han Huck Yang, Jian Zhu, Shinji Watanabe, David R. Mortensen
| Challenge: | Existing evaluations of phone recognition systems only measure surface-level transcription accuracy. |
| Approach: | They propose to standardize transcription-based evaluation and assess downstream utility in clinical, educational, and multilingual settings with transcription and representation probes. |
| Outcome: | The proposed system outperforms LALMs in clinical, educational, and multilingual settings. |
Leveraging Allophony in Self-Supervised Speech Models for Atypical Pronunciation Assessment (2025.naacl-long)
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| Challenge: | Recent phoneme classifiers treat allophonic variation as a single phoneme . atypical pronunciation assessment requires distinguishing between a typical and asymmetric pronunciations . |
| Approach: | They propose a new approach that leverages Gaussian mixture models to model phoneme distributions with multiple subclusters. |
| Outcome: | The proposed approach achieves state-of-the-art across dysarthric and non-native speech datasets. |
PWESuite: Phonetic Word Embeddings and Tasks They Facilitate (2024.lrec-main)
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Vilém Zouhar, Kalvin Chang, Chenxuan Cui, Nate B. Carlson, Nathaniel Romney Robinson, Mrinmaya Sachan, David R. Mortensen
| Challenge: | Existing word embedding methods overlook phonetic information that is crucial for many tasks. |
| Approach: | They propose three methods that use articulatory features to build phonetically informed word embeddings. |
| Outcome: | The proposed methods improve word retrieval and correlation with sound similarity and on rhyme and cognate detection tasks. |
Transformed Protoform Reconstruction (2023.acl-short)
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| Challenge: | Historical linguists reconstruct proto-languages by identifying systematic sound changes that can be inferred from correspondences between attested daughter languages. |
| Approach: | They propose to update their Latin protoform reconstruction model with the Transformer . romance data of 8,000 cognates spanning 5 languages and Chinese dataset are outperformed . |
| Outcome: | The proposed model outperforms previous models on Romance and Chinese datasets. |