Abstract
Previously, we proposed a speaker recognition system using a combination of MFCC-based vocal tract feature and phase information which includes rich vocal source information. In this paper, we investigate the efficiency of combination of various vocal tract features (MFCC and LPCC) and vocal source features (phase and LPC residual) for normal-duration and short-duration utterance. The Japanese Newspaper Article Sentence (JNAS) database was used to evaluate our proposed method. The combination of various vocal tract and vocal source features achieved remarkable improvement than the conventional MFCC-based vocal tract feature for both normal-duration and short-duration utterances.
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