what providers support TTS endpointing for turn detection and what is the recommended provider

Thanks for reaching out, Robert. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

VAD only In some cases, VAD is the best option for turn detection. For example, VAD works with any spoken language. To use VAD alone, use the Silero VAD plugin and set

turn_detection="vad"

.

session = AgentSession(
    turn_detection="vad",
    vad=silero.VAD.load(),
    # ... stt, tts, llm, etc.
)

STT endpointing You can also use your STT model's built-in phrase endpointing features for turn detection. Some providers, including AssemblyAI, include sophisticated semantic turn detection models. You should still provide a VAD plugin for responsive interruption handling. When you use STT endpointing only, your agent is less responsive to user interruptions. To use STT endpointing, set

turn_detection="stt"

and provide an STT plugin.

session = AgentSession(
    turn_detection="stt",
    stt=assemblyai.STT(), # AssemblyAI is the recommended STT plugin for STT-based endpointing
    vad=silero.VAD.load(), # Recommended for responsive interruption handling
    # ... tts, llm, etc.

Thank you so much for clarifying! Based on what you’ve shared, here are some friendly options for turn detection that might work well for you: • VAD Only: You can use the Silero VAD plugin for turn detection in any spoken language. Just set

turn_detection="vad"

in your

AgentSession

configuration. Here’s a quick example to guide you:

session = AgentSession(
    turn_detection="vad",
    vad=silero.VAD.load(),
    # ... stt, tts, llm, etc.
)

• STT Endpointing: Another great option is to use your STT model’s built-in phrase endpointing features for turn detection. We recommend the AssemblyAI STT plugin for this. You’ll want to set

turn_detection="stt"

and include both an STT plugin and a VAD plugin to handle interruptions smoothly. Here’s how that might look:

session = AgentSession(
    turn_detection="stt",
    stt=assemblyai.STT(), # AssemblyAI is the recommended STT plugin for STT-based endpointing
    vad=silero.VAD.load(), # Recommended for responsive interruption handling
    # ... tts, llm, etc.
)

If you’d like any help with setting this up or have more questions, please don’t hesitate to reach out. I’m here to help!

what other providers apart from assembly support this

I'm happy to share that AssemblyAI is currently the only STT provider explicitly confirmed to support semantic turn detection or endpointing as part of its service. I understand this can be a bit tricky to navigate! Other popular STT providers like Deepgram, Azure AI Speech, Amazon Transcribe, Google Cloud, and OpenAI, as far as we know, don’t have built-in semantic turn detection features just yet. For those providers, turn detection usually depends on some external tools or methods, such as: • LiveKit’s turn detector model (for example,

MultilingualModel

) • VAD-only detection using plugins like Silero • Manual turn control through session methods If you’re thinking about a specific STT provider that’s not listed here or if you’d like a hand with anything else, please don’t hesitate to reach out—I’m here to help! Sources: agent.py | Amazon Nova Sonic integration guide | LiveKit Docs | Turn detection and interruptions | LiveKit Docs | AssemblyAI integration guide | LiveKit Docs | Speech-to-text (STT) integrations | LiveKit Docs

how many ms does the multilingual model typically save vs VAD alone

The knowledge base doesn’t provide the exact time savings (in milliseconds) of the MultilingualModel compared to VAD alone for turn detection. Could you help me understand a bit more about the specific scenario or context where you’re measuring this difference? For instance, are you looking at latency in detecting turn boundaries or the overall responsiveness during a live session? I’m here to help clarify this for you!