hf-speech-to-speech-pipeline

To build a real-time speech-to-speech pipeline, you orchestrate VAD, STT, LLM, and TTS components using a queue-based, multi-handler architecture that enforces a consistent setup, process, and cleanup pattern across all stages.

Queue-based communication connects pipeline stages by passing progressive audio chunks between handlers, enabling real-time processing with low latency while supporting on-demand module loading to minimize startup costs.

Yes, the pipeline manages per-session state and optional side data using session lifecycle management patterns, ensuring single-user isolation and preventing cross-session leakage during real-time audio processing.

The best way to minimize startup cost is implementing lazy module loading for on-demand imports, which defers initialization until each pipeline stage is actively required by the queue-based processing flow.

You enforce a consistent processing pattern by applying a BaseHandler contract, which standardizes the setup, process, and cleanup lifecycle phases across all VAD, STT, LLM, and TTS components in the pipeline.

Yes, the architecture supports progressive streaming by processing real-time audio in progressive chunks across queue-wired stages, ensuring low latency for single-user voice agent sessions.