RuASD is a comprehensive Russian speech anti-spoofing dataset featuring 37 synthesis systems and a robustness evaluation pipeline for real-world channel distortions.
ASVspoof 2019: A large-scale public database of synthe- sized, converted and replayed speech
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
Proxy-Anchor metric learning on Wav2Vec2-BERT embeddings with architecture merging achieves 99.76% closed-set accuracy and 2.04% FPR@95 OOD detection on MLAAD v9, doubling prior OOD accuracy on v5 splits.
F5-TTS-DPS integrates EMA and dual-scoring prompt selection into F5-TTS to produce in-the-wild TTS that achieves the best a-DCF scores (0.1582, 0.5233, 0.2562) on three SASV systems in the WildSpoof challenge.
citing papers explorer
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Evaluating Generalization and Robustness in Russian Anti-Spoofing: The RuASD Initiative
RuASD is a comprehensive Russian speech anti-spoofing dataset featuring 37 synthesis systems and a robustness evaluation pipeline for real-world channel distortions.
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Anchoring the Unknown: Open-Set Model Attribution via Proxy-Anchor Learning
Proxy-Anchor metric learning on Wav2Vec2-BERT embeddings with architecture merging achieves 99.76% closed-set accuracy and 2.04% FPR@95 OOD detection on MLAAD v9, doubling prior OOD accuracy on v5 splits.
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Natural Yet Challenging to Detect: Robust In-the-Wild TTS through EMA and Dual-Scoring Prompt Selection -- Submission for WildSpoof 2026 TTS Track
F5-TTS-DPS integrates EMA and dual-scoring prompt selection into F5-TTS to produce in-the-wild TTS that achieves the best a-DCF scores (0.1582, 0.5233, 0.2562) on three SASV systems in the WildSpoof challenge.