voice-agents

To reduce latency in human-AI voice conversations, you can configure a live voice agent that processes speech-to-text, generates LLM responses, and outputs text-to-speech with sub-800ms latency. This supports customer support IVR and virtual assistants requiring natural dialogue.

Speech-to-speech architecture provides the lowest latency for voice agents, while the pipeline architecture (STT→LLM→TTS) offers greater control and debugging capabilities. Both architectures handle real-world voice interactions like customer support and on-call agents.

Voice agents handle barge-in detection and turn-taking using Voice Activity Detection (VAD). Configuring VAD in your voice agent architecture enables robust interactions and natural dialogue for virtual assistants and IVR systems.

Yes, you can build a voice agent with sub-800ms latency using a standard STT, LLM, and TTS pipeline. Applying latency budgeting across the pipeline architecture ensures fast response times for live voice interfaces.

Latency budgeting works across multi-device sessions for virtual assistants. The voice agent architecture supports multi-device session management while maintaining low-latency speech-to-speech and pipeline interactions.

You should avoid speech-to-speech architecture when you need extensive control and debugging for your live voice interface. In these cases, a pipeline architecture (STT→LLM→TTS) is preferred over speech-to-speech despite its higher latency.