Speaker-specific information from residual phase

Abstract

This paper demonstrates the presence of speaker-specific information in the residual phase using autoassociative neural network (AANN) models. The residual phase is extracted from the speech signal after eliminating the vocal tract information by the linear prediction (LP) analysis. AANN models are used for capturing the speaker-specific information present in the residual phase. The speaker recognition studies infer that the residual phase contains significant speaker-specific information and it is indeed captured by the AANN models. In this study we also demonstrate that in voiced speech segments, regions around the instants of glottal closure are more speaker-specific compared to other regions.