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ASVspoof, now in its third edition, is a series of community-led challengeswhich promote the development of countermeasures to protect automatic speakerverification (ASV) from the threat of spoofing. Advances in the 2019 editioninclude: (i) a consideration of both logical access (LA) and physical access(PA) scenarios and the three major forms of spoofing attack, namely synthetic,converted and replayed speech; (ii) spoofing attacks generated withstate-of-the-art neural acoustic and waveform models; (iii) an improved,controlled simulation of replay attacks; (iv) use of the tandem detection costfunction (t-DCF) that reflects the impact of both spoofing and countermeasuresupon ASV reliability. Even if ASV remains the core focus, in retaining theequal error rate (EER) as a secondary metric, ASYspoof also embraces thegrowing importance of fake audio detection. ASVspoof 2019 attracted theparticipation of 63 research teams, with more than half of these reportingsystems that improve upon the performance of two baseline spoofingcountermeasures. This paper describes the 2019 database, protocols andchallenge results. It also outlines major findings which demonstrate the realprogress made in protecting against the threat of spoofing and fake audio.

ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection