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That's a pretty general question. Interruption handling is tricky because it often requires echo cancellation of the voice agent's TTS output. Latency, on the other hand, is all about balancing. A fast STT system should transcribe in under 100ms on a strong GPU, and a decent TTS system adds around 200ms. The rest of the delay comes from LLM generation or speech end detection.
Most basic speech endpoint detection methods rely on waiting for a certain amount of silence, which naturally adds latency.
For better latency:
Make sure your STT, LLM, and TTS are as fast as possible. Use a more advanced speech endpoint detection method, like adjusting the silence threshold based on real-time transcription (e.g., detecting end punctuation) or analyzing frequency changes. People often lower their pitch when finishing a thought or raise it for questions.
For interruption handling:
Remove TTS feedback from the input and apply volume-based thresholds afterward.
Any examples of end to end speech to speech pipeline for better latency and interruption handling?
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