An Audio-Quality-Based Multi-Strategy Approach for Target Speaker Extraction in the Misp 2023 Challenge

Runduo Han, Xiaopeng Yan, Weiming Xu, Pengcheng Guo, Jiayao Sun, He Wang, Quan Lu, Ning Jiang, Lei Xie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper describes our audio-quality-based multi-strategy approach for the audio-visual target speaker extraction (AVTSE) task in the Multi-modal Information based Speech Processing (MISP) 2023 Challenge. Specifically, our approach adopts different extraction strategies based on the audio quality, striking a balance between interference removal and speech preservation, which benifits the back-end automatic speech recognition (ASR) systems. Experiments show that our approach achieves a character error rate (CER) of 24.2% and 33.2% on the Dev and Eval set, respectively, obtaining the second place in the challenge.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-28
Number of pages2
ISBN (Electronic)9798350374513
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 - Seoul, Korea, Republic of
Duration: 14 Apr 202419 Apr 2024

Publication series

Name2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 - Proceedings

Conference

Conference2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024
Country/TerritoryKorea, Republic of
CitySeoul
Period14/04/2419/04/24

Keywords

  • automatic speech recognition
  • target speaker extraction

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