Robust speech recognition using beamforming with adaptive microphone gains and multichannel noise reduction

Shengkui Zhao, Xiong Xiao, Zhaofeng Zhang, Thi Ngoc Tho Nguyen, Xionghu Zhong, Bo Ren, Longbiao Wang, Douglas L. Jones, Eng Siong Chng, Haizhou Li

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

Abstract

This paper presents a robust speech recognition system using a microphone array for the 3rd CHiME Challenge. A minimum variance distortionless response (MVDR) beamformer with adaptive microphone gains is proposed for robust beamforming. Two microphone gain estimation methods are studied using the speech-dominant time-frequency bins. A multichannel noise reduction (MCNR) postprocessing is also proposed to further reduce the interference in the MVDR processed signal. Experimental results for the ChiME-3 challenge show that both the proposed MVDR beamformer with microphone gains and the MCNR postprocessing improve the speech recognition performance significantly. With the state-of-the-art deep neural network (DNN) based acoustic model, our system achieves a word error rate (WER) of 11.67% on the real test data of the evaluation set.

Original languageEnglish (US)
Title of host publication2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages460-467
Number of pages8
ISBN (Electronic)9781479972913
DOIs
StatePublished - Feb 10 2016
Externally publishedYes
EventIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Scottsdale, United States
Duration: Dec 13 2015Dec 17 2015

Publication series

Name2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings

Other

OtherIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015
CountryUnited States
CityScottsdale
Period12/13/1512/17/15

Keywords

  • CHiME 3
  • MVDR beamforming
  • microphone gain
  • multichannel noise reduction
  • robust speech recognition

ASJC Scopus subject areas

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

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  • Cite this

    Zhao, S., Xiao, X., Zhang, Z., Nguyen, T. N. T., Zhong, X., Ren, B., Wang, L., Jones, D. L., Chng, E. S., & Li, H. (2016). Robust speech recognition using beamforming with adaptive microphone gains and multichannel noise reduction. In 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings (pp. 460-467). [7404831] (2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASRU.2015.7404831