ASVspoof: The Automatic Speaker Verification Spoofing and Countermeasures Challenge

• Published in: IEEE journal of selected topics in signal processing Vol. 11; no. 4; pp. 588 - 604
• Main Authors: Zhizheng Wu, Yamagishi, Junichi, Kinnunen, Tomi, Hanilci, Cemal, Sahidullah, Mohammed, Sizov, Aleksandr, Evans, Nicholas, Todisco, Massimiliano, Delgado, Hector
• Format: Journal Article
• Language: English
• Published: IEEE 01.06.2017
• Subjects: ASVspoof; automatic speaker verification; biometric; Computer Science; Data visualization; presentation attacks; Protocols; Signal processing algorithms; Speech; Speech synthesis; spoofing; Vocoders
• ISSN: 1932-4553; 1941-0484
• DOI: 10.1109/JSTSP.2017.2671435

Concerns regarding the vulnerability of automatic speaker verification (ASV) technology against spoofing can undermine confidence in its reliability and form a barrier to exploitation. The absence of competitive evaluations and the lack of common datasets has hampered progress in developing effective spoofing countermeasures. This paper describes the ASV Spoofing and Countermeasures (ASVspoof) initiative, which aims to fill this void. Through the provision of a common dataset, protocols, and metrics, ASVspoof promotes a sound research methodology and fosters technological progress. This paper also describes the ASVspoof 2015 dataset, evaluation, and results with detailed analyses. A review of postevaluation studies conducted using the same dataset illustrates the rapid progress stemming from ASVspoof and outlines the need for further investigation. Priority future research directions are presented in the scope of the next ASVspoof evaluation planned for 2017.