The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study. - Daniel S. Park; Jascha Sohl-Dickstein; Quoc V. Le; Samuel L. Smith (ICML, 2019)

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. - Daniel S. Park; William Chan; Yu Zhang 033; Chung-Cheng Chiu; Barret Zoph; Ekin D. Cubuk; Quoc V. Le (INTERSPEECH, 2019)

Specaugment on Large Scale Datasets. - Daniel S. Park; Yu Zhang 033; Chung-Cheng Chiu; Youzheng Chen; Bo Li 028; William Chan; Quoc V. Le; Yonghui Wu (ICASSP, 2020)

Improved Noisy Student Training for Automatic Speech Recognition. - Daniel S. Park; Yu Zhang 033; Ye Jia; Wei Han 002; Chung-Cheng Chiu; Bo Li 028; Yonghui Wu; Quoc V. Le (INTERSPEECH, 2020)

Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition. - Yu Zhang 033; James Qin; Daniel S. Park; Wei Han 002; Chung-Cheng Chiu; Ruoming Pang; Quoc V. Le; Yonghui Wu (CoRR, 2020)

Towards NNGP-guided Neural Architecture Search. - Daniel S. Park; Jaehoon Lee 001; Daiyi Peng; Yuan Cao; Jascha Sohl-Dickstein (CoRR, 2020)

Efficient Knowledge Distillation for RNN-Transducer Models. - Sankaran Panchapagesan; Daniel S. Park; Chung-Cheng Chiu; Yuan Shangguan; Qiao Liang 001; Alexander Gruenstein (ICASSP, 2021)

SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network. - William Chan; Daniel S. Park; Chris A. Lee; Yu Zhang 033; Quoc V. Le; Mohammad Norouzi 002 (CoRR, 2021)

Universal Paralinguistic Speech Representations Using self-Supervised Conformers. - Joel Shor; Aren Jansen; Wei Han 002; Daniel S. Park; Yu Zhang 033 (ICASSP, 2022)

G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. - Gary Wang; Ekin D. Cubuk; Andrew Rosenberg; Shuyang Cheng; Ron J. Weiss; Bhuvana Ramabhadran; Pedro J. Moreno 001; Quoc V. Le; Daniel S. Park (SLT, 2022)

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. - Yu Zhang 033; Daniel S. Park; Wei Han 002; James Qin; Anmol Gulati; Joel Shor; Aren Jansen; Yuanzhong Xu; Yanping Huang; Shibo Wang; Zongwei Zhou; Bo Li 028; et al. (IEEE J. Sel. Top. Signal Process., 2022)

Large-Scale Language Model Rescoring on Long-Form Data. - Tongzhou Chen; Cyril Allauzen; Yinghui Huang; Daniel S. Park; David Rybach; W. Ronny Huang; Rodrigo Cabrera; Kartik Audhkhasi; Bhuvana Ramabhadran; Pedro J. Moreno 001; Michael Riley 001 (ICASSP, 2023)

Discovering Adaptable Symbolic Algorithms from Scratch. - Stephen Kelly; Daniel S. Park; Xingyou Song; Mitchell McIntire; Pranav Nashikkar; Ritam Guha; Wolfgang Banzhaf; Kalyanmoy Deb; Vishnu Naresh Boddeti; Jie Tan 001; Esteban Real (IROS, 2023)

Noise2Music: Text-conditioned Music Generation with Diffusion Models. - Qingqing Huang; Daniel S. Park; Tao Wang; Timo I. Denk; Andy Ly; Nanxin Chen; Zhengdong Zhang; Zhishuai Zhang; Jiahui Yu; Christian Havnø Frank; Jesse H. Engel; Quoc V. Le; et al. (CoRR, 2023)

Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages. - Yu Zhang 033; Wei Han 002; James Qin; Yongqiang Wang; Ankur Bapna; Zhehuai Chen; Nanxin Chen; Bo Li 028; Vera Axelrod; Gary Wang; Zhong Meng; Ke Hu; et al. (CoRR, 2023)

GridDER: Grid Detection and Evaluation in R. - Xiao Feng; Tainá Rocha; Hanna T. Thammavong; Rima Tulaiha; Xin Chen; Yingying Xie; Daniel S. Park (Ecol. Informatics, 2024)