activity
20172021
most citedLarge-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone

3 citations · 6 across the 3 of their papers we have counts for

collaborators

8 papers

eess.AS20213 cited

Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone

Naoyuki Kanda, Guoli Ye, Yu Wu +5

Transcribing meetings containing overlapped speech with only a single distant microphone (SDM) has been one of the most challenging problems for automatic speech recognition (ASR).…

eess.AS20212 cited

End-to-End Speaker-Attributed ASR with Transformer

Naoyuki Kanda, Guoli Ye, Yashesh Gaur +4

This paper presents our recent effort on end-to-end speaker-attributed automatic speech recognition, which jointly performs speaker counting, speech recognition and speaker identif…

eess.AS2020

Low Latency End-to-End Streaming Speech Recognition with a Scout Network

Chengyi Wang, Yu Wu, Shujie Liu +4

The attention-based Transformer model has achieved promising results for speech recognition (SR) in the offline mode. However, in the streaming mode, the Transformer model usually…

cs.CL2019

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…

cs.CL2018

Advancing Acoustic-to-Word CTC Model with Attention and Mixed-Units

Amit Das, Jinyu Li, Guoli Ye +2

The acoustic-to-word model based on the Connectionist Temporal Classification (CTC) criterion is a natural end-to-end (E2E) system directly targeting word as output unit. Two issue…

cs.CL2018

Developing Far-Field Speaker System Via Teacher-Student Learning

Jinyu Li, Rui Zhao, Zhuo Chen +4

In this study, we develop the keyword spotting (KWS) and acoustic model (AM) components in a far-field speaker system. Specifically, we use teacher-student (T/S) learning to adapt…