ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan
H\'ector Delgado, Nicholas Evans, Tomi Kinnunen, Kong Aik Lee, Xuechen, Liu, Andreas Nautsch, Jose Patino, Md Sahidullah, Massimiliano Todisco, Xin, Wang, Junichi Yamagishi

TL;DR
The ASVspoof 2021 challenge aims to advance research in detecting spoofed and deepfake speech for automatic speaker verification systems through a comprehensive evaluation framework.
Contribution
This paper presents the detailed evaluation plan and dataset for the 2021 ASVspoof challenge, fostering progress in spoofing detection methods.
Findings
Established standardized evaluation protocols
Provided baseline systems and datasets
Facilitated community benchmarking
Abstract
The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and the development of countermeasures. ASVspoof 2021 is the 4th in a series of bi-annual, competitive challenges where the goal is to develop countermeasures capable of discriminating between bona fide and spoofed or deepfake speech. This document provides a technical description of the ASVspoof 2021 challenge, including details of training, development and evaluation data, metrics, baselines, evaluation rules, submission procedures and the schedule.
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Taxonomy
TopicsSpeech Recognition and Synthesis · Natural Language Processing Techniques · Voice and Speech Disorders
