2 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
CasNet: Investigating Channel Robustness for Speech Separation
Fan-Lin Wang, Yao-Fei Cheng, Hung-Shin Lee +2
Recording channel mismatch between training and testing conditions has been shown to be a serious problem for speech separation. This situation greatly reduces the separation perfo…
A Training and Inference Strategy Using Noisy and Enhanced Speech as Target for Speech Enhancement without Clean Speech
Li-Wei Chen, Yao-Fei Cheng, Hung-Shin Lee +2
The lack of clean speech is a practical challenge to the development of speech enhancement systems, which means that there is an inevitable mismatch between their training criterio…
Speech-enhanced and Noise-aware Networks for Robust Speech Recognition
Hung-Shin Lee, Pin-Yuan Chen, Yao-Fei Cheng +2
Compensation for channel mismatch and noise interference is essential for robust automatic speech recognition. Enhanced speech has been introduced into the multi-condition training…
Chain-based Discriminative Autoencoders for Speech Recognition
Hung-Shin Lee, Pin-Tuan Huang, Yao-Fei Cheng +1
In our previous work, we proposed a discriminative autoencoder (DcAE) for speech recognition. DcAE combines two training schemes into one. First, since DcAE aims to learn encoder-d…