40 citations · 89 across the 12 of their papers we have counts for
12 papers
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting
Shubo Lv, Xiong Wang, Sining Sun +2
Real-world complex acoustic environments especially the ones with a low signal-to-noise ratio (SNR) will bring tremendous challenges to a keyword spotting (KWS) system. Inspired by…
Two Stage Contextual Word Filtering for Context bias in Unified Streaming and Non-streaming Transducer
Zhanheng Yang, Sining Sun, Xiong Wang +3
It is difficult for an E2E ASR system to recognize words such as entities appearing infrequently in the training data. A widely used method to mitigate this issue is feeding contex…
CaTT-KWS: A Multi-stage Customized Keyword Spotting Framework based on Cascaded Transducer-Transformer
Zhanheng Yang, Sining Sun, Jin Li +4
Customized keyword spotting (KWS) has great potential to be deployed on edge devices to achieve hands-free user experience. However, in real applications, false alarm (FA) would be…
Leveraging Acoustic Contextual Representation by Audio-textual Cross-modal Learning for Conversational ASR
Kun Wei, Yike Zhang, Sining Sun +2
Leveraging context information is an intuitive idea to improve performance on conversational automatic speech recognition(ASR). Previous works usually adopt recognized hypotheses o…
Conversational Speech Recognition By Learning Conversation-level Characteristics
Kun Wei, Yike Zhang, Sining Sun +2
Conversational automatic speech recognition (ASR) is a task to recognize conversational speech including multiple speakers. Unlike sentence-level ASR, conversational ASR can natura…
Improving Streaming Transformer Based ASR Under a Framework of Self-supervised Learning
Songjun Cao, Yueteng Kang, Yanzhe Fu +4
Recently self-supervised learning has emerged as an effective approach to improve the performance of automatic speech recognition (ASR). Under such a framework, the neural network…