13 citations · 17 across the 6 of their papers we have counts for
6 papers
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…
Improving Accent Identification and Accented Speech Recognition Under a Framework of Self-supervised Learning
Keqi Deng, Songjun Cao, Long Ma
Recently, self-supervised pre-training has gained success in automatic speech recognition (ASR). However, considering the difference between speech accents in real scenarios, how t…
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…
Improving Speech Recognition Accuracy of Local POI Using Geographical Models
Songjun Cao, Yike Zhang, Xiaobing Feng +1
Nowadays voice search for points of interest (POI) is becoming increasingly popular. However, speech recognition for local POI has remained to be a challenge due to multi-dialect a…
Multi-head Monotonic Chunkwise Attention For Online Speech Recognition
Baiji Liu, Songjun Cao, Sining Sun +2
The attention mechanism of the Listen, Attend and Spell (LAS) model requires the whole input sequence to calculate the attention context and thus is not suitable for online speech…