3 citations · 6 across the 10 of their papers we have counts for
5 papers · 1 filter
Transliterated Zero-Shot Domain Adaptation for Automatic Speech Recognition
Han Zhu, Gaofeng Cheng, Qingwei Zhao +1
The performance of automatic speech recognition models often degenerates on domains not covered by the training data. Domain adaptation can address this issue, assuming the availab…
Alternative Pseudo-Labeling for Semi-Supervised Automatic Speech Recognition
Han Zhu, Dongji Gao, Gaofeng Cheng +3
When labeled data is insufficient, semi-supervised learning with the pseudo-labeling technique can significantly improve the performance of automatic speech recognition. However, p…
Online Hybrid CTC/Attention End-to-End Automatic Speech Recognition Architecture
Haoran Miao, Gaofeng Cheng, Pengyuan Zhang +1
Recently, there has been increasing progress in end-to-end automatic speech recognition (ASR) architecture, which transcribes speech to text without any pre-trained alignments. One…
Improving non-autoregressive end-to-end speech recognition with pre-trained acoustic and language models
Keqi Deng, Zehui Yang, Shinji Watanabe +3
While Transformers have achieved promising results in end-to-end (E2E) automatic speech recognition (ASR), their autoregressive (AR) structure becomes a bottleneck for speeding up…
Transformer-based Online CTC/attention End-to-End Speech Recognition Architecture
Haoran Miao, Gaofeng Cheng, Changfeng Gao +2
Recently, Transformer has gained success in automatic speech recognition (ASR) field. However, it is challenging to deploy a Transformer-based end-to-end (E2E) model for online spe…