Generalized cyclic transformations in speaker-independent speech recognition

Abstract

A feature extraction method is presented that is robust against vocal tract length changes. It uses the generalized cyclic transformations primarily used within the field of pattern recognition. In matching training and testing conditions the resulting accuracies are comparable to the ones of MFCCs. However, in mismatching training and testing conditions with respect to the mean vocal tract length the presented features significantly outperform the MFCCs.