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BUT Systems and Analyses for the ASVspoof 5 Challenge

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arxiv 2408.11152 v1 pith:I5EOKVSK submitted 2024-08-20 cs.SD eess.AS

Johan Rohdin , Lin Zhang , Oldřich Plchot , Vojtěch Staněk , David Mihola , Junyi Peng , Themos Stafylakis , Dmitriy Beveraki
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Anna Silnova Jan Brukner Lukáš Burget
This is my paper · ORCID
classification cs.SDeess.AS
keywords speakeranalysesasvspoofautomaticchallengeinformationsasvscores
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper describes the BUT submitted systems for the ASVspoof 5 challenge, along with analyses. For the conventional deepfake detection task, we use ResNet18 and self-supervised models for the closed and open conditions, respectively. In addition, we analyze and visualize different combinations of speaker information and spoofing information as label schemes for training. For spoofing-robust automatic speaker verification (SASV), we introduce effective priors and propose using logistic regression to jointly train affine transformations of the countermeasure scores and the automatic speaker verification scores in such a way that the SASV LLR is optimized.

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  1. Tandem spoofing-robust automatic speaker verification based on time-domain embeddings

    eess.AS 2024-12 conditional novelty 3.0 of 10

    A gender-separated countermeasure built from probability-mass-function time embeddings improves tandem spoofing-robust speaker verification on ASVspoof2019, but only when thresholds are tuned on the evaluation set.

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