arXiv:2607. 03985v1 Announce Type: cross Abstract: Advanced neural technologies in speech synthesis and voice conversion (VC) have introduced severe risks to personal privacy, necessitating robust Speaker Anonymization Systems (SAS).
By Meiying Melissa Chen, Anastasia Kuznetsova, Zhenyu Wang, Zhiyao Duan
arXiv:2603. 10725v3 Announce Type: replace-cross Abstract: The modern generative audio models can be used by an adversary in an unlawful manner, specifically, to impersonate other people to gain access to private information.
By Artem Dvirniak, Evgeny Kushnir, Dmitrii Tarasov, Artem Iudin, Oleg Kiriukhin, Mikhail Pautov, Dmitrii Korzh, Oleg Y. Rogov
We’re sharing lessons from a small scale preview of Voice Engine, a model for creating custom voices.
arXiv:2606. 03686v1 Announce Type: new Abstract: We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent.
By Sarah Barrington, Maty Bohacek, Hany Farid
arXiv:2607. 03418v1 Announce Type: cross Abstract: A trustworthy and GDPR-compliant deepfake audio detector must base its decisions on acoustic artifacts, not on what is being said or who is speaking.
By Nicolas M. M\"uller, Aditya Tirumala Bukkapatnam, Dominik Schnieders, Zohaib Ahmed
arXiv:2603. 14033v2 Announce Type: replace-cross Abstract: Audio anti-spoofing systems are typically trained to assign one authenticity label to an entire speech utterance.
By Shree Harsha Bokkahalli Satish, Harm Lameris, Joakim Gustafson, \'Eva Sz\'ekely