Voice AI Latency: What Causes Delays and How to Fix Them
Blog post from Coval
Voice AI latency, a critical issue for conversational AI systems, significantly affects user experience and system performance. Even a slight delay between a caller's speech and the AI agent's response can lead to misunderstandings and user dissatisfaction. The latency arises from multiple layers in the voice AI processing pipeline, including network transport, Voice Activity Detection (VAD), Speech-to-Text (STT), Large Language Model (LLM) inference, and Text-to-Speech (TTS) synthesis. Each layer contributes to the overall delay, with LLM inference typically being the largest contributor. Optimizing these processes through techniques like streaming, adaptive VAD, and strategic model selection is essential for minimizing latency and ensuring smooth and natural interactions. Effective latency measurement and continuous monitoring across these layers are vital for maintaining system efficiency and preventing user frustration or call drop-offs.
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