Large Audio Language Models for Spoofing-Aware Speaker Verification
Recent advances in text-to-speech and voice cloning make high-quality spoofing inexpensive and scalable, threatening voice authentication systems, especially automatic speaker verification (ASV). Existing defenses mainly address this threat through binary countermeasures (CMs) for deepfake detection or spoofing-aware speaker verification (SASV), where current systems are dominated by modular ASV-CM fusion and cascaded pipelines. Although large audio language models (LALMs) have shown promise on related audio tasks, including CM and ASV, their use for SASV remains unexplored, despite their capacity to produce natural-language rationales for auditing and robustness beyond discriminative pre...
| Authors | Sofya Savelyeva, Mariia Perunova, Evgeny Kushnir et al. |
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| Primary category | cs.SD |
| Published | 16 July 2026 |
| Last updated at source | 16 July 2026 |
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