Analysis and Comparison of Score Normalisation Methods for Text-Dependent Speaker Verification

Abstract

This paper presents an investigation into the relative effectiveness of various score normalisation methods for speaker verification. The study provides a thorough analysis of different approaches for normalising verification scores, and comparatively examines these under identical experimental conditions. The experiments are based on the use of subsets of the Brent (telephone quality) speech database, consisting of repetitions of isolated digit utterances zero to nine spoken by native English speakers. Based on the experimental results it is demonstrated that amongst the considered methods, a particular form of the cohort normalisation method provides the best performance in terms of the verification accuracy. The paper discusses details of the experimental study and presents an analysis of the results.