80 citations · 199 across the 17 of their papers we have counts for
7 papers · 1 filter
Deploying self-supervised learning in the wild for hybrid automatic speech recognition
Mostafa Karimi, Changliang Liu, Kenichi Kumatani +3
Self-supervised learning (SSL) methods have proven to be very successful in automatic speech recognition (ASR). These great improvements have been reported mostly based on highly c…
AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario
Yihui Fu, Luyao Cheng, Shubo Lv +10
In this paper, we present AISHELL-4, a sizable real-recorded Mandarin speech dataset collected by 8-channel circular microphone array for speech processing in conference scenario.…
Multi-Channel Automatic Speech Recognition Using Deep Complex Unet
Yuxiang Kong, Jian Wu, Quandong Wang +4
The front-end module in multi-channel automatic speech recognition (ASR) systems mainly use microphone array techniques to produce enhanced signals in noisy conditions with reverbe…
DESNet: A Multi-channel Network for Simultaneous Speech Dereverberation, Enhancement and Separation
Yihui Fu, Jian Wu, Yanxin Hu +2
In this paper, we propose a multi-channel network for simultaneous speech dereverberation, enhancement and separation (DESNet). To enable gradient propagation and joint optimizatio…
Continuous speech separation: dataset and analysis
Zhuo Chen, Takuya Yoshioka, Liang Lu +6
This paper describes a dataset and protocols for evaluating continuous speech separation algorithms. Most prior studies on speech separation use pre-segmented signals of artificial…
End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang +6
The end-to-end approach for single-channel speech separation has been studied recently and shown promising results. This paper extended the previous approach and proposed a new end…