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Publications

Publications (1st author)

  • Li, Xinjian, et al. "Question Answering System for Entrance Exams in QA4MRE." CLEF (Working Notes). 2013

  • Dalmia, S*, Li, X* et al. "Domain robust feature extraction for rapid low resource asr development." 2018 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2018. (* equal contribution)

  • Li, Xinjian, et al. "Multilingual Speech Recognition with Corpus Relatedness Sampling." Proc. Interspeech 2019 (2019): 2120-2124.

  • Li, Xinjian, et al. "SANTLR: Speech Annotation Toolkit for Low Resource Languages." Proc. Interspeech 2019 (2019): 3681-3682.

  • Li, Xinjian, et al. "Towards zero-shot learning for automatic phonemic transcription." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34. No. 05. 2020.

  • Li, Xinjian, et al. "Universal phone recognition with a multilingual allophone system." ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020.

  • Li, Xinjian, et al. "Phone Distribution Estimation for Low Resource Languages." ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021.

  • Li, Xinjian, et al. "Multilingual phonetic dataset for low resource speech recognition." ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021.

  • Li, Xinjian, et al. "Hierarchical Phone Recognition with Compositional Phonetics." Interspeech. 2021.

  • Li, Xinjian, et al. "Zero-shot Learning for Grapheme to Phoneme Conversion with Language Ensemble." Findings of the Association for Computational Linguistics: ACL 2022. 2022. [pdf]

  • Li, Xinjian, et al. "Phone Inventories and Recognition for Every Language" LREC 2022. 2022

  • Li, Xinjian, et al. "ASR2K: Speech Recognition for Around 2000 Languages without Audio" Interspeech 2022. 2022

Publications (others)

  • Li, J., Qu, Sh., Wang, Y., Li, X., Das,S., Metze, F., Music Theory Inspired Policy Gradient Method for Piano Music Transcription NeurIPS 2018 Workshop

  • Yao, J., Li, X., Fiscato, M., Ohtsuki, K., JLM - Fast RNN Language Model with Large Vocabulary. ANLP 2019

  • Yao, J., Shu, R., Li, X., Ohtsuki, K., Nakayama, H., Real-time Neural-Based Input Method NACCL 2019

  • Dalmia, S., Li, X., Black, A. W., Metze, F., Phoneme Level Language Models for Sequence Based Low Resrouce ASR ICASSP 2019

  • Li, S Qu, X Li, J Szurley, JZ Kolter, F Metze. Adversarial Music: Real World Audio Adversary Against Wake-word Detection System NeurIPS 2019

  • Dong, Fengquan, et al. "Machine listening for heart status monitoring: Introducing and benchmarking hss—the heart sounds shenzhen corpus." IEEE journal of biomedical and health informatics 24.7 (2019): 2082-2092.

  • Mortensen, David R., et al. "AlloVera: A Multilingual Allophone Database." Proceedings of the 12th Language Resources and Evaluation Conference. 2020.

  • Neubig, Graham, et al. "A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization." LREC 2020 Workshop Language Resources and Evaluation Conference 11–16 May 2020.

  • Qiu, Zimeng, et al. "Towards Context-Aware End-to-End Code-Switching Speech Recognition." Proc. Interspeech 2020 (2020): 4776-4780.

  • Huang, Wen-Chin, et al. "On Prosody Modeling for ASR+ TTS based Voice Conversion." 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). IEEE, 2021.

  • Gupta, Akshat, et al. "Acoustics based intent recognition using discovered phonetic units for low resource languages." ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021.

  • Siminyu, Kathleen, et al. "Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties." Interspeech. 2021.

  • Mortensen, David R., et al. "Tusom2021: A phonetically transcribed speech dataset from an endangered language for universal phone recognition experiments." Interspeech. 2021.

  • Li, Juncheng B., et al. "On adversarial robustness of large-scale audio visual learning." ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. (Best Student Paper)