arXiv:2606.05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only a single task such as streaming ASR or voice chatting. It is time to unify them into one online LALM: a model that, through an always-on perceive-decide-respond loop, listens to sound, environment, and instructions in real time and reacts on the fly. We formalize this regime as the Audio Interaction Model, and realize it with Audio-Interaction, a unified streaming model that retains offline task e
The proliferation of Large Audio Language Models and streaming audio applications creates a clear need for unified, interactive models to overcome current fragmentation and offline limitations.
This development represents a significant step towards truly autonomous AI agents capable of real-time, context-aware audio interaction, impacting numerous sectors from customer service to robotics.
Audio interaction models will transition from discrete, task-specific systems to integrated, online LALMs that can dynamically perceive, decide, and respond across various audio inputs and tasks.
- · AI agents developers
- · Audio hardware manufacturers
- · Customer service platforms
- · Robotics companies
- · Fragmented single-task audio AI companies
- · Legacy offline audio processing solutions
The advent of unified Audio Interaction Models paves the way for more natural and seamless human-AI audio communication.
This could enable advanced AI partners and interfaces that adapt to real-time environmental and conversational cues.
Ubiquitous, contextually aware audio AI might alter human communication patterns and expectations for digital interaction.
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Read at arXiv cs.AI