PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Unified Framework for Score Normalization Techniques Applied to Text Independent Speaker Verification
Johnny Mariéthoz and Samy Bengio
IEEE Signal Processing Letters Volume 12, Number 7, pp. 532-535, 2005.

Abstract

The purpose of this paper is to unify several of the state-of-the-art score normalization techniques applied to text-independent speaker verification systems. We propose a new framework for this purpose. The two well-known Z- and T-normalization techniques can be easily interpreted in this framework as different ways to estimate score distributions. This is useful as it helps to understand the various assumptions behind these well-known score normalization techniques, and opens the door for yet more complex solutions. Finally, some experiments on the Switchboard database are performed in order to illustrate the validity of the new proposed framework.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Speech
ID Code:1099
Deposited By:Samy Bengio
Deposited On:26 September 2005