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arXiv · 1508.01746

Using Deep Learning for Detecting Spoofing Attacks on Speech Signals

Alan Godoy·Flávio Simões·José Augusto Stuchi·Marcus de Assis Angeloni·Mário Uliani·Ricardo Violato
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Abstract

It is well known that speaker verification systems are subject to spoofing attacks. The Automatic Speaker Verification Spoofing and Countermeasures Challenge -- ASVSpoof2015 -- provides a standard spoofing database, containing attacks based on synthetic speech, along with a protocol for experiments. This paper describes CPqD's systems submitted to the ASVSpoof2015 Challenge, based on deep neural networks, working both as a classifier and as a feature extraction module for a GMM and a SVM classifier. Results show the validity of this approach, achieving less than 0.5\% EER for known attacks.

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BibTeXRIS

Alan Godoy, Flávio Simões, José Augusto Stuchi, Marcus de Assis Angeloni, Mário Uliani, Ricardo Violato. 2015-08-07. Using Deep Learning for Detecting Spoofing Attacks on Speech Signals. https://arxiv.org/abs/1508.01746

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