arXiv:2607. 16870v1 Announce Type: cross Abstract: End-to-end speech language models increasingly represent user speech with speech tokens rather than relying exclusively on cascaded ASR--LLM--TTS pipelines.
By Ye Lu, Yihan Yan, Zhaoyang Zhang, Zhitao Ou, Runze Liu, Li Liu, Shen Wang
The paper investigates how acoustic and content-oriented speaker verification attacks perform against multilingual voice anonymization. It evaluates both attacker types on anonymized speech, builds a multilingual voice-converted dataset to enhance cross‑lingual generalization, and finds that attack success depends on how much linguistic utility is preserved. Acoustic‑oriented attacks generally outperform content‑oriented ones, but the performance gap narrows when linguistic information is well maintained, and the new dataset improves results while reducing cross‑lingual disparities.
By Ridwan Arefeen, Ze Li, Rong Tong, Ming Li, Xiaoxiao Miao
The paper introduces the Spectral Masking and Interpolation Attack (SMIA), a black‑box adversarial technique that subtly alters inaudible frequency regions of AI‑generated audio to fool voice authentication systems and their countermeasures. Experiments show SMIA achieves at least 82% success against combined verification and countermeasure systems, 97.5% against standalone speaker verification, and 100% against countermeasures, revealing a critical security gap. The authors argue that current static defenses are inadequate and call for dynamic, context‑aware defenses that can adapt to evolving threats.
By Kamel Kamel, Hridoy Sankar Dutta, Keshav Sood, Sunil Aryal
arXiv:2608. 10405v1 Announce Type: cross Abstract: Many studies have shown that specially crafted inputs can induce large language models (LLMs) to generate excessively long outputs, resulting in significant computational overhead and resource consumption.
By Shuozhe Cheng, Kunlan Xiang, Mingxuan Li, Ji Zhang, Dongxiao Liu, Wenbo Jiang
arXiv:2610.27210v1 Announce Type: new
Abstract: Speech models are increasingly used as an interface to AI systems, from transcription tools to voice agents. Existing audio backdoors require an attack...
By Nata\v{s}a Kr\v{c}o, Euodia Dodd, Peter Romov, Yves-Alexandre de Montjoye
The paper introduces a black-box membership inference attack framework tailored for fine-tuned text-to-speech models, addressing challenges in query generation and representation engineering. It evaluates five query types, finding recitation queries most effective, and uses multi-level speech embeddings with temporal alignment for fine-grained comparison. Experiments on CosyVoice2, F5-TTS, and XTTS-v2 trained on VCTK and British Dialect datasets show high privacy leakage, with speaker-level AUC above 0.80 and record-level AUC between 0.80 and 0.90.
By Kunlin Cai, Kaiyuan Zhang, Zihang Xiang, Jinghuai Zhang, Abeer Alwan, Fnu Suya, Yuan Tian