Automatic Speech Verification Spoofing Detection

TL;DR

This paper discusses developing robust countermeasures for automatic speech verification spoofing detection, emphasizing security and efficiency, evaluated using EER and t-DCF metrics.

Contribution

It introduces potential countermeasures for ASV spoofing detection aligned with ASVSpoof 2019 standards, focusing on robustness and efficiency.

Findings

Countermeasures evaluated with EER and t-DCF metrics.

Enhanced robustness against spoofing attacks.

Improved efficiency in detection methods.

Abstract

Automatic speech verification (ASV) is the technology to determine the identity of a person based on their voice. While being convenient for identity verification, we should aim for the highest system security standard given that it is the safeguard of valuable digital assets. Bearing this in mind, we follow the setup in ASVSpoof 2019 competition to develop potential countermeasures that are robust and efficient. Two metrics, EER and t-DCF, will be used for system evaluation.