10 citations · 14 across the 6 of their papers we have counts for
4 papers · 1 filter
Exploiting Single-Channel Speech For Multi-channel End-to-end Speech Recognition
Keyu An, Zhijian Ou
Recently, the end-to-end training approach for neural beamformer-supported multi-channel ASR has shown its effectiveness in multi-channel speech recognition. However, the integrati…
Deformable TDNN with adaptive receptive fields for speech recognition
Keyu An, Yi Zhang, Zhijian Ou
Time Delay Neural Networks (TDNNs) are widely used in both DNN-HMM based hybrid speech recognition systems and recent end-to-end systems. Nevertheless, the receptive fields of TDNN…
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through Gradients
Huahuan Zheng, Keyu An, Zhijian Ou
Neural Architecture Search (NAS), the process of automating architecture engineering, is an appealing next step to advancing end-to-end Automatic Speech Recognition (ASR), replacin…
CAT: A CTC-CRF based ASR Toolkit Bridging the Hybrid and the End-to-end Approaches towards Data Efficiency and Low Latency
Keyu An, Hongyu Xiang, Zhijian Ou
In this paper, we present a new open source toolkit for speech recognition, named CAT (CTC-CRF based ASR Toolkit). CAT inherits the data-efficiency of the hybrid approach and the s…