Publications

**Yi-Te Hsu**, Sarthak Garg, Yi-Hsiu Liao and Ilya Chatsviorkin. Efficient Inference For Neural Machine Translation. accepted to SustaiNLP Workshop at EMNLP 2020, 2020.

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Yu-Chen Lin, **Yi-Te Hsu**, Szu-Wei Fu, Yu Tsao, and Tei-Wei Kuo. IA-NET: Acceleration and Compression of Speech Enhancement using Integer-adder Deep Neural Network. accepted to Annual Conference of the International Speech Communication Association (INTERSPEECH 2019), 2019.

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Bai Li, **Yi-Te Hsu** and Frank Rudzicz. Detecting dementia in Mandarin Chinese using transfer learning from a parallel corpus. accepted to Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019), 2018.

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**Yi-Te Hsu**, Zining Zhu, Chi-Te Wang, Shih-Hau Fang, Frank Rudzicz and Yu Tsao. Robustness against the channel effect in pathological voice detection. accepted to Machine Learning for Health Workshop at NIPS 2018, 2018.

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**Yi-Te Hsu**, Yu-Chen Lin, Szu-Wei Fu, Yu Tsao, and Tei-Wei Kuo. A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN). accepted to IEEE Spoken Language Technology conference (IEEE SLT), 2018.

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Zong-Ying Chuang, Xiao-Tong Yu, Chen Ji-Ying, Yi-Te Hsu, Zhe-Zhuang Xu, Chi-Te Wang, Feng-Chuan Lin, and Shih-Hau Fang. DNN-based Approach to Detect and Classify Pathological Voice. accepted to FEMH Voice Data Challenge at IEEE International Conference on Big Data (IEEE Big Data 2018), 2018.