  The ASVspoof initiative was conceived to spearhead research in anti-spoofing
for automatic speaker verification (ASV). This paper describes the third in a
series of bi-annual challenges: ASVspoof 2019. With the challenge database and
protocols being described elsewhere, the focus of this paper is on results and
the top performing single and ensemble system submissions from 62 teams, all of
which out-perform the two baseline systems, often by a substantial margin.
Deeper analyses shows that performance is dominated by specific conditions
involving either specific spoofing attacks or specific acoustic environments.
While fusion is shown to be particularly effective for the logical access
scenario involving speech synthesis and voice conversion attacks, participants
largely struggled to apply fusion successfully for the physical access scenario
involving simulated replay attacks. This is likely the result of a lack of
system complementarity, while oracle fusion experiments show clear potential to
improve performance. Furthermore, while results for simulated data are
promising, experiments with real replay data show a substantial gap, most
likely due to the presence of additive noise in the latter. This finding, among
others, leads to a number of ideas for further research and directions for
future editions of the ASVspoof challenge.
