A speech enhancement approach E-CMN/CSS for speech recognition in car environments

Abstract

This paper proposes the robust speech enhancement approach E-CMN (Exact Cepstrum Mean Normalization)/CSS (Continuous Spectral Subtraction). The E-CMN, which we proposed for compensation of multiplicative distortions (Shozakai et al., 1997), calculates two cepstrum mean vectors, one for speech for each speaker and the other for non-speech for each environment. The CSS subtracts continuously average spectra at every frame. A high robustness of the proposed method is clarified by comparative evaluation with alternative methods for speech recognition tasks in car environments.