Cluster and Intrinsic Dimensionality Analysis of the Modified Group Delay Feature for Speaker Classification

Speakers are generally identified by using features derived from the Fourier transform magnitude. The Modified group delay feature(MODGDF) derived from the Fourier transform phase has been used effectively for speaker recognition in our previous efforts.Although the efficacy of the MODGDF as an alternative to the MFCC is yet to be established, it has been shown in our earlier work that composite features derived from the MFCC and MODGDF perform extremely well. In this paper we investigate the cluster structures of speakers derived using the MODGDF in the lower dimensional feature space. Three non linear dimensionality reduction techniques The Sammon mapping, ISOMAP and LLE are used to visualize speaker clusters in the lower dimensional feature space. We identify the intrinsic dimensionality of both the MODGDF and MFCC using the Elbow technique. We also present the results of speaker identification experiments performed using MODGDF, MFCC and composite features derived from the MODGDF and MFCC.

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