Zhizheng Wu, Junichi Yamagishi, Tomi Kinnunen, Cemal Hanilci, Md Sahidullah, Aleksandr Sizov, Nicholas Evans, Massimiliano Todisco and Hector Delgado
IEEE Journal of Selected Topics in Signal Processing, Vol. 11, No. 4, pp. 588-604, June 2017
Abstract: 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 post-evaluation 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.