Heartbeat Thinking: Speculative Reasoning and Tool Execution While Listening in Realtime Voice Agents
Tool-using voice agents often leave users waiting after speech ends, even when actionable information arrives earlier in the request. Speculative approaches begin work during speech, but chunk-bounded or interrupt-on-update generation can truncate a tool call before its arguments are complete. This couples computation time to speech updates, limiting useful work completed in ad
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Tool-using voice agents often leave users waiting after speech ends, even when actionable information arrives earlier in the request. Speculative approaches begin work during speech, but chunk-bounded or interrupt-on-update generation can truncate a tool call before its arguments are complete. This couples computation time to speech updates, limiting useful work completed in ad
This paper introduces a novel approach to real-time voice agent reasoning and tool execution, addressing the critical challenge of latency and responsiveness. For ML engineers, understanding 'Heartbeat Thinking' is crucial for developing more natural and efficient conversational AI systems, directly impacting user experience in voice-enabled applications.