Summary on the ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge-Reference-Cited by-同舟云学术

Summary on the ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
language:
Short-container-title:

Author:

Yu Fan¹,Zhang Shiliang¹,Guo Pengcheng²,Fu Yihui²,Du Zhihao¹,Zheng Siqi¹,Huang Weilong¹,Xie Lei²,Tan Zheng-Hua³,Wang DeLiang⁴,Qian Yanmin⁵,Lee Kong Aik⁶,Yan Zhijie¹,Ma Bin⁷,Xu Xin⁸,Bu Hui⁸

Affiliation:

1. Alibaba Group,Speech Lab,China

2. AISHELL Foundation

3. Aalborg University,Department of Electronic Systems,Aalborg,Denmark

4. The Ohio State University,Center for Cognitive and Brain Sciences,Department of Computer Science and Engineering,USA

5. Shanghai Jiao Tong University,SpeechLab,Department of Computer Science and Engineering,China

6. A*STAR,Institute for Infocomm Research,Aural and Language Intelligence Department,Singapore

7. Alibaba Group,Speech Lab,Singapore

8. Beijing Shell Shell Technology Co., Ltd.,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746270.pdf?arnumber=9746270

Reference55 articles.

1. AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario

2. The AMI meeting corpus;mccowan;Proc ICMT,2005

3. End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend

4. MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition

5. Continuous Speech Separation: Dataset and Analysis

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Second Multi-Channel Multi-Party Meeting Transcription Challenge (M2MeT 2.0): A Benchmark for Speaker-Attributed ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16

2. Sa-Paraformer: Non-Autoregressive End-To-End Speaker-Attributed ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16

3. Robust End-to-End Diarization with Domain Adaptive Training and Multi-Task Learning;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16

4. A Comparative Study on Multichannel Speaker-Attributed Automatic Speech Recognition in Multi-party Meetings;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

5. MFCCA:Multi-Frame Cross-Channel Attention for Multi-Speaker ASR in Multi-Party Meeting Scenario;2022 IEEE Spoken Language Technology Workshop (SLT);2023-01-09