Thanks — you’re asking whether you can (and should) run a separate STT service while using a real-time API + TTS to get better transcripts than the realtime model’s transcripts. Short answer: yes. Why: realtime models do not provide reliable interim transcripts and user transcriptions are often delayed—sometimes arriving only after the agent has already responded. That makes realtime transcripts unsuitable when you need accurate, low-latency transcriptions. Recommended approach (hybrid setup) • Use the realtime model for low-latency audio I/O and TTS (fast voice responses, emotion-aware audio). • Run a dedicated STT service (Deepgram, Google Cloud Speech, OpenAI Whisper, etc.) in parallel to generate accurate, streaming transcripts. • Forward the STT output to your frontend or application in real time, while still letting the realtime model handle voice interaction. Benefits • Accurate, streaming transcripts for UI, logging, or analytics. • Low-latency conversational audio from the realtime API (so voice interactions remain snappy). • You can use the STT transcript for downstream tasks (search, QA, compliance) even if realtime transcripts arrive late. Implementation notes / things to consider • Synchronization: attach timestamps or sequence IDs so you can align STT transcripts with audio events or agent responses. • Bandwidth & costs: running an external STT stream in addition to realtime audio will increase usage and cost—factor this into architecture decisions. • Privacy & data flow: ensure your data handling and any forwarding of audio/text meets your compliance requirements. • Where to integrate in LiveKit: configure your AgentSession (or equivalent) so the realtime model handles LLM/audio I/O while a separate STT plugin handles transcription only. If you want, tell me: • Which STT provider you’re considering, and • Whether you need streaming (interim results) or post-call batch transcripts. I can then give concrete integration steps, example architecture, or tips for timestamp alignment and cost optimization. Sources: Realtime models overview | LiveKit Documentation