The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines

Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

253 Citations (Scopus)

Abstract

The CHiME challenge series aims to advance far field speech recognition technology by promoting research at the interface of signal processing and automatic speech recognition. This paper presents the design and outcomes of the 3rd CHiME Challenge, which targets the performance of automatic speech recognition in a real-world, commercially-motivated scenario: a person talking to a tablet device that has been fitted with a six-channel microphone array. The paper describes the data collection, the task definition and the baseline systems for data simulation, enhancement and recognition. The paper then presents an overview of the 26 systems that were submitted to the challenge focusing on the strategies that proved to be most successful relative to the MVDR array processing and DNN acoustic modeling reference system. Challenge findings related to the role of simulated data in system training and evaluation are discussed.

Original languageEnglish
Title of host publication2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages504-511
Number of pages8
ISBN (Electronic)9781479972913
DOIs
Publication statusPublished - 2016 Feb 10
Externally publishedYes
EventIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Scottsdale, United States
Duration: 2015 Dec 132015 Dec 17

Other

OtherIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015
CountryUnited States
CityScottsdale
Period15/12/1315/12/17

Fingerprint

Speech recognition
Array processing
Microphones
Signal processing
Acoustics

Keywords

  • 'CHiME' challenge
  • microphone array
  • Noise-robust ASR

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

Cite this

Barker, J., Marxer, R., Vincent, E., & Watanabe, S. (2016). The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines. In 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings (pp. 504-511). [7404837] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASRU.2015.7404837

The third 'CHiME' speech separation and recognition challenge : Dataset, task and baselines. / Barker, Jon; Marxer, Ricard; Vincent, Emmanuel; Watanabe, Shinji.

2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 504-511 7404837.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Barker, J, Marxer, R, Vincent, E & Watanabe, S 2016, The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines. in 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings., 7404837, Institute of Electrical and Electronics Engineers Inc., pp. 504-511, IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015, Scottsdale, United States, 15/12/13. https://doi.org/10.1109/ASRU.2015.7404837
Barker J, Marxer R, Vincent E, Watanabe S. The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines. In 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 504-511. 7404837 https://doi.org/10.1109/ASRU.2015.7404837
Barker, Jon ; Marxer, Ricard ; Vincent, Emmanuel ; Watanabe, Shinji. / The third 'CHiME' speech separation and recognition challenge : Dataset, task and baselines. 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 504-511
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