39 citations · 143 across the 12 of their papers we have counts for
4 papers · 1 filter
Semantic Mask for Transformer based End-to-End Speech Recognition
Chengyi Wang, Yu Wu, Yujiao Du +7
Attention-based encoder-decoder model has achieved impressive results for both automatic speech recognition (ASR) and text-to-speech (TTS) tasks. This approach takes advantage of t…
Accelerating Transformer Decoding via a Hybrid of Self-attention and Recurrent Neural Network
Chengyi Wang, Shuangzhi Wu, Shujie Liu
Due to the highly parallelizable architecture, Transformer is faster to train than RNN-based models and popularly used in machine translation tasks. However, at inference time, eac…
Source Dependency-Aware Transformer with Supervised Self-Attention
Chengyi Wang, Shuangzhi Wu, Shujie Liu
Recently, Transformer has achieved the state-of-the-art performance on many machine translation tasks. However, without syntax knowledge explicitly considered in the encoder, incor…
Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation
Chengyi Wang, Yu Wu, Shujie Liu +2
End-to-end speech translation, a hot topic in recent years, aims to translate a segment of audio into a specific language with an end-to-end model. Conventional approaches employ m…