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  • Research Article
  • Open Access

Multi-Channel Sub-Band Speech Recognition

EURASIP Journal on Advances in Signal Processing20012001:569196

https://doi.org/10.1155/S1110865701000154

  • Received: 22 December 2000
  • Published:

Abstract

Two distinct fields of research into robust speech recognition are the use of microphone arrays for signal enhancement and the use of independent frequency sub-band models for robust recognition. In this article, we propose and investigate the integration of these two techniques on two different levels. First, a broad-band beamforming microphone array allows for natural integration with sub-band speech recognition as the beamformer is implemented as a combination of band-limited sub-arrays. Rather than recombining the sub-array outputs to give a single enhanced output, we fuse the output of separate hidden Markov models trained on each sub-array frequency band. Second, a dynamic sub-band weighting algorithm is proposed in which the cross- and auto-spectral densities of the microphone inputs are used to estimate the reliability of each frequency band. The proposed multi-channel sub-band system is evaluated on an isolated digit recognition task and compared to both a standard full-band microphone array system and a single channel sub-band system.

Keywords

  • microphone array
  • sub-band
  • beamforming
  • speech recognition

Authors’ Affiliations

(1)
Speech Research Laboratory, RCSAVT, School of EESE, Queensland University of Technology, GPO Box 2434, Brisbane, QLD, 4001, Australia

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