Unverified80% confidenceFactTime unknown
语音AI系统中的中断处理需要在毫秒级别内完成停止TTS音频流、丢弃未播放内容、重置LLM上下文状态、重新进入STT监听模式等操作
1
Sources
80%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
Dogra: Open-Source Self-Hosted Voice AI Platform — Say Goodbye to VAPI's Sky-High Bills
bilibili比特光锥_BightCone
Related Entities
Related Claims
UnverifiedIn voice dialogue systems, the LLM inference step requires the time to first token (TTFT) to be kept within 200 milliseconds; otherwise, users will noticeably perceive a pause.78% similarUnverifiedThe core challenges of implementing full-duplex voice AI include running ASR and TTS simultaneously, real-time acoustic echo cancellation (AEC), and controlling end-to-end latency to within 150 milliseconds.76% similarUnverified传统语音AI采用串行管线设计，即VAD→ASR→LLM→TTS四个独立模块依次传递数据，每个环节引入约100-300毫秒延迟，四段叠加总延迟往往超过1秒75% similarUnverifiedEnd-to-end voice processing architectures process audio tokens directly within a unified model, with theoretical latency compressible to within 200ms.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/10346API
curl https://kongchang.com/api/v1/knowledge/claims/10346MCP
get_claim(id=10346)