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    <abstract>Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. This transition, however, introduces a distinct class of vulnerabilities that remain largely uncharacterized. We examine the security implications of this modality shift by designing a text-to-audio jailbreak that embeds disallowed directives within a narrative-style audio stream. The attack leverages an advanced instruction-following text-to-speech (TTS) model to exploit structural and acoustic properties, thereby circumventing safety mechanisms primarily calibrated for text. When delivered through synthetic speech, the narrative format elicits restricted outputs from state-of-the-art models, including Gemini 2.0 Flash, achieving a 98.26% success rate that substantially exceeds text-only baselines. These results highlight the need for safety frameworks that jointly reason over linguistic and paralinguistic representations, particularly as speech-based interfaces become more prevalent.</abstract>
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%0 Conference Proceedings
%T Now You Hear Me: Audio Narrative Attacks Against Large Audio–Language Models
%A Yu, Ye
%A Jin, Haibo
%A Yu, Yaoning
%A Zhuang, Jun
%A Wang, Haohan
%Y Demberg, Vera
%Y Inui, Kentaro
%Y Marquez, Lluís
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-380-7
%F yu-etal-2026-now
%X Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. This transition, however, introduces a distinct class of vulnerabilities that remain largely uncharacterized. We examine the security implications of this modality shift by designing a text-to-audio jailbreak that embeds disallowed directives within a narrative-style audio stream. The attack leverages an advanced instruction-following text-to-speech (TTS) model to exploit structural and acoustic properties, thereby circumventing safety mechanisms primarily calibrated for text. When delivered through synthetic speech, the narrative format elicits restricted outputs from state-of-the-art models, including Gemini 2.0 Flash, achieving a 98.26% success rate that substantially exceeds text-only baselines. These results highlight the need for safety frameworks that jointly reason over linguistic and paralinguistic representations, particularly as speech-based interfaces become more prevalent.
%U https://aclanthology.org/2026.eacl-long.278/
%P 5925-5939

Markdown (Informal)

[Now You Hear Me: Audio Narrative Attacks Against Large Audio–Language Models](https://aclanthology.org/2026.eacl-long.278/) (Yu et al., EACL 2026)

• Now You Hear Me: Audio Narrative Attacks Against Large Audio–Language Models (Yu et al., EACL 2026)

ACL

• Ye Yu, Haibo Jin, Yaoning Yu, Jun Zhuang, and Haohan Wang. 2026. Now You Hear Me: Audio Narrative Attacks Against Large Audio–Language Models. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5925–5939, Rabat, Morocco. Association for Computational Linguistics.