most citedAASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge

1 citations · 3 across the 10 of their papers we have counts for

collaborators
Showing cs.SDShow all

6 papers · 1 filter

cs.SD2026

Training-Free Model Selection and Domain-Aware Score Calibration for First-Shot Anomalous Sound Detection

Grach Mkrtchian

First-shot anomalous sound detection in DCASE Challenge Task 2 must flag anomalies of unseen machine types with a single threshold, without knowing whether a test clip comes from t…

cs.SD2026

When Spoof Detectors Travel: Evaluation Across 66 Languages in the Low-Resource Language Spoofing Corpus

Kirill Borodin, Vasiliy Kudryavtsev, Maxim Maslov +2

We introduce LRLspoof, a large-scale multilingual synthetic-speech corpus for cross-lingual spoof detection, comprising 2,732 hours of audio generated with 24 open-source TTS syste…

cs.SD20261 cited

AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge

Kirill Borodin, Vasiliy Kudryavtsev, Dmitrii Korzh +4

Automatic Speaker Verification (ASV) systems, which identify speakers based on their voice characteristics, have numerous applications, such as user authentication in financial tra…

cs.SD2026

Evaluating Generalization and Robustness in Russian Anti-Spoofing: The RuASD Initiative

Ksenia Lysikova, Kirill Borodin, Grach Mkrtchian

RuASD (Russian AntiSpoofing Dataset) is a dedicated, reproducible benchmark for Russian-language speech anti-spoofing designed to evaluate both in-domain discrimination and robustn…

cs.SD20261 cited

Interpreting Multi-Branch Anti-Spoofing Architectures: Correlating Internal Strategy with Empirical Performance

Ivan Viakhirev, Kirill Borodin, Mikhail Gorodnichev +1

Multi-branch deep neural networks like AASIST3 achieve state-of-the-art comparable performance in audio anti-spoofing, yet their internal decision dynamics remain opaque compared t…

cs.SD2026

Combining Masked Language Modeling and Cross-Modal Contrastive Learning for Prosody-Aware TTS

Kirill Borodin, Vasiliy Kudryavtsev, Maxim Maslov +3

We investigate multi-stage pretraining for prosody modeling in diffusion-based TTS. A speaker-conditioned dual-stream encoder is trained with masked language modeling followed by S…