10 citations · 11 across the 2 of their papers we have counts for
5 papers
SEOFP-NET: Compression and Acceleration of Deep Neural Networks for Speech Enhancement Using Sign-Exponent-Only Floating-Points
Yu-Chen Lin, Cheng Yu, Yi-Te Hsu +3
Numerous compression and acceleration strategies have achieved outstanding results on classification tasks in various fields, such as computer vision and speech signal processing.…
Efficient Inference For Neural Machine Translation
Yi-Te Hsu, Sarthak Garg, Yi-Hsiu Liao +1
Large Transformer models have achieved state-of-the-art results in neural machine translation and have become standard in the field. In this work, we look for the optimal combinati…
Detecting dementia in Mandarin Chinese using transfer learning from a parallel corpus
Bai Li, Yi-Te Hsu, Frank Rudzicz
Machine learning has shown promise for automatic detection of Alzheimer's disease (AD) through speech; however, efforts are hampered by a scarcity of data, especially in languages…
Robustness against the channel effect in pathological voice detection
Yi-Te Hsu, Zining Zhu, Chi-Te Wang +3
Many people are suffering from voice disorders, which can adversely affect the quality of their lives. In response, some researchers have proposed algorithms for automatic assessme…
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)
Yi-Te Hsu, Yu-Chen Lin, Szu-Wei Fu +2
Numerous studies have investigated the effectiveness of neural network quantization on pattern classification tasks. The present study, for the first time, investigated the perform…