rapid-honey-43838
02/27/2026, 5:19 PMtall-airline-16756
02/27/2026, 5:19 PMtall-airline-16756
02/27/2026, 5:19 PMelevenlabs/eleven_flash_v2
◦ elevenlabs/eleven_flash_v2_5
◦ elevenlabs/eleven_turbo_v2
◦ elevenlabs/eleven_turbo_v2_5
◦ elevenlabs/eleven_multilingual_v2
• You can specify ElevenLabs TTS when creating an agent session either with a string descriptor:
◦ Example: tts="elevenlabs/eleven_turbo_v2_5:Xb7hH8MSUJpSbSDYk0k2"
• Or with the inference.TTS class for more control:
◦ Example:
from livekit.agents import inference
session = AgentSession(
tts=inference.TTS(
model="elevenlabs/eleven_turbo_v2_5",
voice="Xb7hH8MSUJpSbSDYk0k2",
language="en"
),
# ... other parameters
)
Voices and languages
• LiveKit supports all default ElevenLabs voices (examples: Alice, Chris, Eric, Jessica).
• Several models support multilingual output — eleven_flash_v2_5, eleven_turbo_v2_5, and eleven_multilingual_v2 support 30+ languages including English, Spanish, French, German, Hindi, and more.
What’s not supported here
• Custom, community, or cloned voices from ElevenLabs are not supported through LiveKit Inference. To use those, you must connect your own ElevenLabs account via the ElevenLabs plugin.
Billing and auth
• No separate ElevenLabs API key is required when using LiveKit Inference. Usage is billed through your LiveKit Cloud invoice.
Would you like:
• Help choosing a model/voice for a specific language or use case (IVR, narration, real‑time agent voice, etc.)?
• An example for integrating ElevenLabs TTS into a specific AgentSession flow or SDK (web, Python, or else)?
I’m happy to walk through an example matched to your use case.
Sources: Introducing LiveKit Inference: A unified model interface for voice AI | ElevenLabs TTS plugin guide | LiveKit Documentation | ElevenLabs TTS | LiveKit Documentationrapid-honey-43838
02/27/2026, 6:06 PMtall-airline-16756
02/27/2026, 6:06 PMfrom livekit.plugins.turn_detector.multilingual import MultilingualModel
session = AgentSession(
turn_detection=MultilingualModel(),
stt=inference.STT(language="en"),
# ... other parameters
)
1. Download model weights before deployment:
• Python: uv run agent.py download-files
• Node.js: pnpm run download-files
If you’d like, I can:
• Walk through integrating this into a specific SDK (web, Python, or Node).
• Help pick STT settings to pair with the turn detector for best English performance.
• Share troubleshooting tips if you see false positives or missed turn ends.
Which of those would help you most right now?
Sources: Building the all-in-one platform for voice AI agents | Updating the Turn Detector Model | LiveKit | Improved End-of-Turn Model Cuts Voice AI Interruptions 39% | LiveKit turn detector plugin | LiveKit Documentation | Improving voice AI's turn detection with transformers