DNN-based Approach to Detect and Classify Pathological Voice. - Zong-Ying Chuang; Xiao-Tong Yu; Ji-Ying Chen; Yi-Te Hsu; Zhezhuang Xu; Chi-Te Wang; Feng-Chuan Lin; Shih-Hau Fang (IEEE BigData, 2018)

A Study on Speech Enhancement Using Exponent-Only Floating Point Quantized Neural Network (EOFP-QNN). - Yi-Te Hsu; Yu-Chen Lin 003; Szu-Wei Fu; Yu Tsao 001; Tei-Wei Kuo (SLT, 2018)

Robustness against the channel effect in pathological voice detection. - Yi-Te Hsu; Zining Zhu 001; Chi-Te Wang; Shih-Hau Fang; Frank Rudzicz; Yu Tsao 001 (CoRR, 2018)

IA-NET: Acceleration and Compression of Speech Enhancement Using Integer-Adder Deep Neural Network. - Yu-Chen Lin 003; Yi-Te Hsu; Szu-Wei Fu; Yu Tsao 001; Tei-Wei Kuo (INTERSPEECH, 2019)

Detecting dementia in Mandarin Chinese using transfer learning from a parallel corpus. - Bai Li; Yi-Te Hsu; Frank Rudzicz (NAACL-HLT (1), 2019)

Efficient Inference For Neural Machine Translation. - Yi-Te Hsu; Sarthak Garg; Yi-Hsiu Liao; Ilya Chatsviorkin (SustaiNLP@EMNLP, 2020)

SEOFP-NET: Compression and Acceleration of Deep Neural Networks for Speech Enhancement Using Sign-Exponent-Only Floating-Points. - Yu-Chen Lin 003; Cheng Yu; Yi-Te Hsu; Szu-Wei Fu; Yu Tsao 001; Tei-Wei Kuo (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Generative Context-Aware Fine-Tuning of Self-Supervised Speech Models. - Suwon Shon; Kwangyoun Kim; Prashant Sridhar; Yi-Te Hsu; Shinji Watanabe 001; Karen Livescu (ICASSP, 2024)

Convolution-Augmented Parameter-Efficient Fine-Tuning for Speech Recognition. - Kwangyoun Kim; Suwon Shon; Yi-Te Hsu; Prashant Sridhar; Karen Livescu; Shinji Watanabe 001 (INTERSPEECH, 2024)

DiscreteSLU: A Large Language Model with Self-Supervised Discrete Speech Units for Spoken Language Understanding. - Suwon Shon; Kwangyoun Kim; Yi-Te Hsu; Prashant Sridhar; Shinji Watanabe 001; Karen Livescu (INTERSPEECH, 2024)