13 citations · 35 across the 23 of their papers we have counts for
6 papers · 1 filter
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…
Censer: Curriculum Semi-supervised Learning for Speech Recognition Based on Self-supervised Pre-training
Bowen Zhang, Songjun Cao, Xiaoming Zhang +3
Recent studies have shown that the benefits provided by self-supervised pre-training and self-training (pseudo-labeling) are complementary. Semi-supervised fine-tuning strategies u…
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling
Yike Zhang, Xiaobing Feng, Yi Liu +2
Automatic speech recognition (ASR) systems used on smart phones or vehicles are usually required to process speech queries from very different domains. In such situations, a vanill…
Improving CTC-based speech recognition via knowledge transferring from pre-trained language models
Keqi Deng, Songjun Cao, Yike Zhang +4
Recently, end-to-end automatic speech recognition models based on connectionist temporal classification (CTC) have achieved impressive results, especially when fine-tuned from wav2…
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…