387 citations · 630 across the 10 of their papers we have counts for
8 papers · 1 filter
Accelerating RNN-T Training and Inference Using CTC guidance
Yongqiang Wang, Zhehuai Chen, Chengjian Zheng +3
We propose a novel method to accelerate training and inference process of recurrent neural network transducer (RNN-T) based on the guidance from a co-trained connectionist temporal…
Unsupervised Data Selection via Discrete Speech Representation for ASR
Zhiyun Lu, Yongqiang Wang, Yu Zhang +3
Self-supervised learning of speech representations has achieved impressive results in improving automatic speech recognition (ASR). In this paper, we show that data selection is im…
FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization
Jiahui Yu, Chung-Cheng Chiu, Bo Li +8
Streaming automatic speech recognition (ASR) aims to emit each hypothesized word as quickly and accurately as possible. However, emitting fast without degrading quality, as measure…
Conformer: Convolution-augmented Transformer for Speech Recognition
Anmol Gulati, James Qin, Chung-Cheng Chiu +8
Recently Transformer and Convolution neural network (CNN) based models have shown promising results in Automatic Speech Recognition (ASR), outperforming Recurrent neural networks (…
ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context
Wei Han, Zhengdong Zhang, Yu Zhang +6
Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper…
Improved Noisy Student Training for Automatic Speech Recognition
Daniel S. Park, Yu Zhang, Ye Jia +5
Recently, a semi-supervised learning method known as "noisy student training" has been shown to improve image classification performance of deep networks significantly. Noisy stude…