Robust speech recognition for car environment noise

Abstract

AbstractA method for handling noise in a car information machine incorporating speech recognition middleware and having a SuperH (SH) Micon as its platform is reported. Using both a noise acoustic model and a spectral subtraction scheme, this method is evaluated by computer simulation against an evaluation database constructed by considering the usage environment and the microphone position. In evaluations using the noise model alone, a speech recognition rate of 11.0% in a test track driving environment was obtained when an HMM tutored by speech without noise was used, while a recognition rate of 82.7% was obtained when an HMM constructed by superimposing noise over the tutoring speech was used. The speech recognition rate was improved by about an additional 5%, to 87.6%, by using this noise‐containing acoustic model and the spectral subtraction scheme. In addition, when speech recognition middleware incorporated with the antinoise method was loaded on an SH board, a recognition performance comparable with the computer simulation results was obtained. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 85(11): 65–73, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10055