I totally understand how it can be a bit tricky when VAD detects speech but Deepgram doesn’t provide a transcript. Here’s a friendly approach you can try to handle this smoothly: • Validate Transcripts: It’s a good idea to make sure your logic only processes transcripts that are final and not empty. For example:

@session.on("user_input_transcribed")
def on_transcript(event):
    if event.is_final and event.transcript.strip():
        print(f"User said: {event.transcript}")

• Tune VAD Settings: You might want to adjust settings like

min_speech_duration

and

min_silence_duration

to help reduce any false triggers. • Implement User Feedback: Consider using a timer to show a friendly "listening" indicator when VAD detects speech. If no transcript comes through within a certain time frame (like 5-10 seconds), you can clear the indicator so the user isn’t left wondering. These steps can really help create a smooth and reassuring experience for your users while gracefully handling those tricky edge cases. If you have any questions or want to chat more about this, I’m here to help! Sources: tests/test_stt.py | Working with plugins | LiveKit Docs | Speech-to-text (STT) integrations | LiveKit Docs | Speech & Audio Processing | livekit/livekit_composite | DeepWiki | basics/echo_transcriber_agent.py