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Robust Distant Speech Recognition by Combining Multiple Microphone-Array Processing with Position-Dependent CMN

  • Longbiao WangEmail author
  • Norihide Kitaoka
  • Seiichi Nakagawa
Open Access
Research Article
Part of the following topical collections:
  1. Multisensor Processing for Signal Extraction and Applications

Abstract

We propose robust distant speech recognition by combining multiple microphone-array processing with position-dependent cepstral mean normalization (CMN). In the recognition stage, the system estimates the speaker position and adopts compensation parameters estimated a priori corresponding to the estimated position. Then the system applies CMN to the speech (i.e., position-dependent CMN) and performs speech recognition for each channel. The features obtained from the multiple channels are integrated with the following two types of processings. The first method is to use the maximum vote or the maximum summation likelihood of recognition results from multiple channels to obtain the final result, which is called multiple-decoder processing. The second method is to calculate the output probability of each input at frame level, and a single decoder using these output probabilities is used to perform speech recognition. This is called single-decoder processing, resulting in lower computational cost. We combine the delay-and-sum beamforming with multiple-decoder processing or single-decoder processing, which is termed multiple microphone-array processing. We conducted the experiments of our proposed method using a limited vocabulary (100 words) distant isolated word recognition in a real environment. The proposed multiple microphone-array processing using multiple decoders with position-dependent CMN achieved a 3.2% improvement (50% relative error reduction rate) over the delay-and-sum beamforming with conventional CMN (i.e., the conventional method). The multiple microphone-array processing using a single decoder needs about one-third the computational time of that using multiple decoders without degrading speech recognition performance.

Keywords

Word Recognition Speech Recognition Recognition Performance Multiple Channel Lower Computational Cost 

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Copyright information

© Longbiao Wang et al. 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Longbiao Wang
    • 1
    Email author
  • Norihide Kitaoka
    • 1
  • Seiichi Nakagawa
    • 1
  1. 1.Department of Information and Computer SciencesToyohashi University of TechnologyToyahashi-shiJapan

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