Using Deep Learning for Detecting Spoofing Attacks on Speech Signals

Understand

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.