Class-Discriminative Weighted Distortion Measure for VQ-based Speaker Identification

Authors:
Tomi Kinnunen;Ismo Kärkkäinen
Affiliations:
-;-
Venue:
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2002

Citing 4
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Abstract

We consider the distortion measure in vector quantization based speaker identification system. The model of a speaker is a codebook generated from the set of feature vectors from the speakers voice sample. The matching is performed by evaluating the distortions between the unknown speech sample and the models in the speaker database. In this paper, we introduce a weighted distortion measure that takes into account the correlations between the known models in the database. Larger weights are assigned to vectors that have high discriminating power between the speakers and vice versa.