Normalization of speaker variability by spectrum warping for robust speech recognition

This paper examines techniques for normalization of unseen speakers in recognition. Two implementations of linear spectrum warping were examined: time domain resampling and filter bank scaling. It is shown that for seen speakers, the models trained by unwarped utterances are less sensitive to spectrum warping by filter bank scaling than by resampling. A… (More)