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Author manuscript, published in "International Conference on Biometrics: Theory, Applications and Systems (BTAS) (2013) 8p" A One-Class Classification Approach to Generalised Speaker Verification Spoofing Countermeasures using Local Binary Patterns (2013)
BibTeX
@MISC{Alegre13authormanuscript,,
author = {Federico Alegre and Asmaa Amehraye and Nicholas Evans},
title = {Author manuscript, published in "International Conference on Biometrics: Theory, Applications and Systems (BTAS) (2013) 8p" A One-Class Classification Approach to Generalised Speaker Verification Spoofing Countermeasures using Local Binary Patterns},
year = {2013}
}
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Abstract
The vulnerability of automatic speaker verification systems to spoofing is now well accepted. While recent work has shown the potential to develop countermeasures capable of detecting spoofed speech signals, existing solutions typically function well only for specific attacks on which they are optimised. Since the exact nature of spoofing attacks can never be known in practice, there is thus a need for generalised countermeasures which can detect previously unseen spoofing attacks. This paper presents a novel countermeasure based on the analysis of speech signals using local binary patterns followed by a one-class classification approach. The new countermeasure captures differences in the spectro-temporal texture of genuine and spoofed speech, but relies only on a model of the former. We report experiments with three different approaches to spoofing and with a state-of-the-art i-vector speaker verification system which uses probabilistic linear discriminant analysis for intersession compensation. While a support vector machine classifier is tuned with examples of converted voice, it delivers reliable detection of spoofing attacks using synthesized speech and artificial signals, attacks for which it is not optimised. 1.
Keyphrases
local binary pattern one-class classification approach speaker verification spoofing countermeasure international conference author manuscript different approach recent work artificial signal specific attack converted voice automatic speaker verification system reliable detection new countermeasure capture difference probabilistic linear discriminant analysis novel countermeasure speech signal support vector machine classifier intersession compensation spectro-temporal texture exact nature spoofed speech spoofed speech signal state-of-the-art i-vector speaker verification system generalised countermeasure
