A Practical Guide to Logical Access Voice Presentation Attack Detection

Abstract

Voice-based human-machine interfaces with an automatic speaker verification (ASV) component are commonly used in the market. However, the threat from presentation attacks is also growing since attackers can use recent speech synthesis technology to produce a naturalsounding voice of a victim. Presentation attack detection (PAD) for ASV, or speech anti-spoofing, is therefore indispensable. Research on voice PAD has seen significant progress since the early 2010s, including the advancement in PAD models, benchmark datasets, and evaluation campaigns. This chapter presents a practical guide to the field of voice PAD, with a focus on logical access attacks using text-to-speech and voice conversion algorithms and spoofing countermeasures based on artifact detection. It introduces the basic concept of voice PAD, explains the common techniques, and provides an experimental study using recent methods on a benchmark dataset. Code for the experiments is open-sourced.

SASV Challenge 2022: A Spoofing Aware Speaker Verification Challenge Evaluation Plan

“…Led by the ASVspoof initiative and corresponding challenge series, countermeasure (CM) systems have hence been developed in order to help detect and deflect spoofing attacks [8][9][10]. In the case of a logical access, telephony scenario involving only TTS and VC attacks, the best performing spoofing CM systems can deliver EERs of less than 2% [11][12][13][14][15][16][17][18][19][20][21].…”