A Comparison of Supervised and Unsupervised Pre-Training of End-to-End Models. - Ananya Misra; Dongseong Hwang; Zhouyuan Huo; Shefali Garg; Nikhil Siddhartha; Arun Narayanan; Khe Chai Sim (Interspeech, 2021)

Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device. - Zhouyuan Huo; Dongseong Hwang; Khe Chai Sim; Shefali Garg; Ananya Misra; Nikhil Siddhartha; Trevor Strohman; Françoise Beaufays (CoRR, 2021)

Large-Scale ASR Domain Adaptation Using Self- and Semi-Supervised Learning. - Dongseong Hwang; Ananya Misra; Zhouyuan Huo; Nikhil Siddhartha; Shefali Garg; David Qiu; Khe Chai Sim; Trevor Strohman; Françoise Beaufays; Yanzhang He (ICASSP, 2022)

A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes. - Shaojin Ding; Weiran Wang; Ding Zhao; Tara N. Sainath; Yanzhang He; Robert David; Rami Botros; Xin Wang 016; Rina Panigrahy; Qiao Liang 001; Dongseong Hwang; Ian McGraw; et al. (INTERSPEECH, 2022)

Incremental Layer-Wise Self-Supervised Learning for Efficient Unsupervised Speech Domain Adaptation On Device. - Zhouyuan Huo; Dongseong Hwang; Khe Chai Sim; Shefali Garg; Ananya Misra; Nikhil Siddhartha; Trevor Strohman; Françoise Beaufays (INTERSPEECH, 2022)

Pseudo Label Is Better Than Human Label. - Dongseong Hwang; Khe Chai Sim; Zhouyuan Huo; Trevor Strohman (INTERSPEECH, 2022)

Efficient Cascaded Streaming ASR System Via Frame Rate Reduction. - Xingyu Cai; David Qiu; Shaojin Ding; Dongseong Hwang; Weiran Wang; Antoine Bruguier; Rohit Prabhavalkar; Tara N. Sainath; Yanzhang He (ASRU, 2023)

Resource-Efficient Transfer Learning from Speech Foundation Model Using Hierarchical Feature Fusion. - Zhouyuan Huo; Khe Chai Sim; Bo Li 028; Dongseong Hwang; Tara N. Sainath; Trevor Strohman (ICASSP, 2023)

Comparison of Soft and Hard Target RNN-T Distillation for Large-Scale ASR. - Dongseong Hwang; Khe Chai Sim; Yu Zhang 033; Trevor Strohman (ICASSP, 2023)

Efficient Domain Adaptation for Speech Foundation Models. - Bo Li 028; Dongseong Hwang; Zhouyuan Huo; Junwen Bai; Guru Prakash; Tara N. Sainath; Khe Chai Sim; Yu Zhang 033; Wei Han 002; Trevor Strohman; Françoise Beaufays (ICASSP, 2023)

Revisiting the Entropy Semiring for Neural Speech Recognition. - Oscar Chang; Dongseong Hwang; Olivier Siohan (ICLR, 2023)

Re-investigating the Efficient Transfer Learning of Speech Foundation Model using Feature Fusion Methods. - Zhouyuan Huo; Khe Chai Sim; Dongseong Hwang; Tsendsuren Munkhdalai; Tara N. Sainath; Pedro Moreno Mengibar (INTERSPEECH, 2023)

Modular Domain Adaptation for Conformer-Based Streaming ASR. - Qiujia Li; Bo Li 028; Dongseong Hwang; Tara N. Sainath; Pedro Moreno Mengibar (INTERSPEECH, 2023)

Edit Distance based RL for RNNT decoding. - Dongseong Hwang; Changwan Ryu; Khe Chai Sim (CoRR, 2023)

Massive End-to-end Models for Short Search Queries. - Weiran Wang; Rohit Prabhavalkar; Dongseong Hwang; Qiujia Li; Khe Chai Sim; Bo Li 028; James Qin; Xingyu Cai; Adam Stooke; Zhong Meng; CJ Zheng; Yanzhang He; et al. (CoRR, 2023)

Improving Speech Recognition for African American English with Audio Classification. - Shefali Garg; Zhouyuan Huo; Khe Chai Sim; Suzan Schwartz; Mason Chua; Alëna Aksënova; Tsendsuren Munkhdalai; Levi King; Darryl Wright; Zion Mengesha; Dongseong Hwang; Tara N. Sainath; et al. (ICASSP, 2024)

Extreme Encoder Output Frame Rate Reduction: Improving Computational Latencies of Large End-to-End Models. - Rohit Prabhavalkar; Zhong Meng; Weiran Wang; Adam Stooke; Xingyu Cai; Yanzhang He; Arun Narayanan; Dongseong Hwang; Tara N. Sainath; Pedro J. Moreno 001 (ICASSP, 2024)

AdaRA: Adaptive Rank Allocation of Residual Adapters for Speech Foundation Model. - Zhouyuan Huo; Dongseong Hwang; Gan Song; Khe Chai Sim; Weiran Wang (INTERSPEECH, 2024)

Massive End-to-end Speech Recognition Models with Time Reduction. - Weiran Wang; Rohit Prabhavalkar; Haozhe Shan; Zhong Meng; Dongseong Hwang; Qiujia Li; Khe Chai Sim; Bo Li 028; James Qin; Xingyu Cai; Adam Stooke; Chengjian Zheng; et al. (NAACL-HLT, 2024)

TransformerFAM: Feedback attention is working memory. - Dongseong Hwang; Weiran Wang; Zhuoyuan Huo; Khe Chai Sim; Pedro Moreno Mengibar (CoRR, 2024)

FAdam: Adam is a natural gradient optimizer using diagonal empirical Fisher information. - Dongseong Hwang (CoRR, 2024)

AXLearn: Modular Large Model Training on Heterogeneous Infrastructure. - Mark Lee; Tom Gunter; Chang Lan; John Peebles; Hanzhi Zhou; Kelvin Zou; Sneha Bangalore; Chung-Cheng Chiu; Nan Du; Xianzhi Du; Philipp Dufter; Ruixuan Hou; et al. (CoRR, 2025)