Papers › Tandem spoofing-robust automatic speaker verification based on time-domain embeddings
Tandem spoofing-robust automatic speaker verification based on time-domain embeddings
Avishai Weizman, Yehuda Ben-Shimol, Itshak Lapidot
Spoofing-robust automatic speaker verification (SASV) systems are a crucial technology for the protection against spoofed speech. In this study, we focus on logical access attacks and introduce a novel approach to SASV tasks. A novel representation of genuine and spoofed speech is employed, based on the probability mass function (PMF) of waveform amplitudes in the time domain. This methodology generates novel time embeddings derived from the PMF of selected groups within the training set. This paper highlights the role of gender segregation and its positive impact on performance. We propose a countermeasure (CM) system that employs time-domain embeddings derived from the PMF of spoofed and genuine speech, as well as gender recognition based on male and female time-based embeddings. The method exhibits notable gender recognition capabilities, with mismatch rates of 0.94% and 1.79% for males and females, respectively. The male and female CM systems achieve an equal error rate (EER) of 8.67% and 10.12%, respectively. By integrating this approach with traditional speaker verification systems, we demonstrate improved generalization ability and tandem detection cost function evaluation using the ASVspoof2019 challenge database. Furthermore, we investigate the impact of fusing the time embedding approach with traditional CM and illustrate how this fusion enhances generalization in SASV architectures.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speaker Verification | ASVspoof 2019 - LA | ECAPA-TDNN | minDCF | 0.004 | #1 of 1 | Archive leaderboard | report |
| Voice Anti-spoofing | ASVspoof 2019 - LA | OCSoftmax+GD | EER | 2.62% | #3 of 8 | Archive leaderboard | report |
| Voice Anti-spoofing | ASVspoof 2019 - LA | GD | EER | 9.68% | #5 of 8 | Archive leaderboard | report |
| Voice Anti-spoofing | ASVspoof 2019 - LA | GD | min a-DCF | 0.1684 | #5 of 8 | Archive leaderboard | report |
| Voice Anti-spoofing | ASVspoof 2019 - LA | GD | min t-dcf | 0.2709 | #5 of 8 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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