Deep Residual Neural Networks for Audio Spoofing Detection

Understand

The state-of-art models for speech synthesis and voice conversion are capable of generating synthetic speech that is perceptually indistinguishable from bonafide human speech.

• These methods represent a threat to the automatic speaker verification (ASV) systems.
• Additionally, replay attacks where the attacker uses a speaker to replay a previously recorded genuine human speech are also possible.
• We present our solution for the ASVSpoof2019 competition, which aims to develop countermeasure systems that distinguish between spoofing attacks and genuine speeches.