13 citations · 35 across the 23 of their papers we have counts for
6 papers · 1 filter
Improving Hybrid CTC/Attention End-to-end Speech Recognition with Pretrained Acoustic and Language Model
Keqi Deng, Songjun Cao, Yike Zhang +1
Recently, self-supervised pretraining has achieved impressive results in end-to-end (E2E) automatic speech recognition (ASR). However, the dominant sequence-to-sequence (S2S) E2E m…
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…
Efficient Conformer with Prob-Sparse Attention Mechanism for End-to-EndSpeech Recognition
Xiong Wang, Sining Sun, Lei Xie +1
End-to-end models are favored in automatic speech recognition (ASR) because of their simplified system structure and superior performance. Among these models, Transformer and Confo…
Tiny Transducer: A Highly-efficient Speech Recognition Model on Edge Devices
Yuekai Zhang, Sining Sun, Long Ma
This paper proposes an extremely lightweight phone-based transducer model with a tiny decoding graph on edge devices. First, a phone synchronous decoding (PSD) algorithm based on b…