Researchers developed ERIS, a new framework that uses genetic algorithms to exploit Audio Large Models (ALMs) by disguising malicious instructions as natural speech with background noise. The system can bypass safety filters by embedding harmful content in real-world audio interference that appears harmless to humans and security systems.
Researchers introduced JALMBench, a comprehensive benchmark to evaluate jailbreak vulnerabilities in Large Audio Language Models (LALMs), comprising over 245,000 audio samples and 11,000 text samples. The study reveals that LALMs face significant safety risks from jailbreak attacks, with text-based safety measures only partially transferring to audio inputs, highlighting the need for specialized defense mechanisms.
Google has announced improvements to its Gemini audio models, enhancing voice interaction capabilities for more powerful and natural voice experiences. The upgrades focus on better audio processing and response quality in conversational AI applications.
Developers can now access next-generation audio models through an API that includes advanced text-to-speech capabilities. The new models allow for instructional voice customization, enabling developers to specify speaking styles like 'sympathetic customer service agent' for enhanced voice agent applications.
