livekit-plugins-namo-turn-detector 1.2.18

End of utterance detection for LiveKit Agents

Namo Turn Detector Plugin for LiveKit Agents

Turn detection plugin for LiveKit Agents using Namo Turn Detector models.

Installation

pip install livekit-plugins-namo-turn-detector

or 

pip install .

Features

• Multilingual Support: 23+ languages with unified multilingual model
• Language-Specific Models: Optimized models for English, Vietnamese, Chinese
• Fast & Accurate: Outperforms baseline models in accuracy and speed
• Async API: Built on LiveKit's inference runner for optimal performance
• Easy Integration: Drop-in replacement for existing turn detectors

Quick Start

Multilingual Model (23+ Languages)

from livekit.plugins.namo_turn_detector.multilingual import MultilingualModel
from livekit import agents


async def entrypoint(ctx: agents.JobContext):
    model = MultilingualModel(threshold=0.7)
    
    # Get probability
    prob = await model.predict_end_of_turn(chat_ctx)

Language-Specific Model (Better Accuracy)

from livekit.plugins.namo_turn_detector.language_specific import LanguageSpecificModel

# English model
async def entrypoint(ctx: agents.JobContext):
    model = LanguageSpecificModel(language="en", threshold=0.7)
    prob = await model.predict_end_of_turn(chat_ctx)

Supported Languages: en (English), vi (Vietnamese), zh (Chinese)

Benchmark Results

Comparison across English, Vietnamese, and Chinese:

English Performance

Sample: "Hello, how are you?"
  • Namo Multilingual:     0.8757 (16ms) - EOT: True
  • Namo English-Specific: 0.0002 (13ms) - EOT: False
  • LiveKit Multilingual:  0.2838 (33ms) - EOT: True
  • LiveKit English:       0.4596 (4ms)  - EOT: True

Sample: "What's the weather like today?"
  • Namo Multilingual:     0.8032 (15ms) - EOT: True
  • Namo English-Specific: 0.9999 (9ms)  - EOT: True ⭐
  • LiveKit Multilingual:  0.7799 (27ms) - EOT: True
  • LiveKit English:       0.9409 (3ms)  - EOT: True

Vietnamese Performance

Sample: "Xin chào, bạn khỏe không?" (Hello, how are you?)
  • Namo Multilingual:        0.8651 (25ms) - EOT: True
  • Namo Vietnamese-Specific: 0.9857 (36ms) - EOT: True ⭐
  • LiveKit Multilingual:     0.0322 (20ms) - EOT: False

Sample: "Thời tiết hôm nay thế nào?" (What's the weather today?)
  • Namo Multilingual:        0.5168 (27ms) - EOT: False
  • Namo Vietnamese-Specific: 0.9952 (4ms)  - EOT: True ⭐
  • LiveKit Multilingual:     0.2988 (22ms) - EOT: False

Sample: "Vay ở đâu" (Where to borrow) - Incomplete phrase
  • Namo Multilingual:        0.6599 (20ms) - EOT: False
  • Namo Vietnamese-Specific: 0.9875 (10ms) - EOT: True ⭐
  • LiveKit Multilingual:     0.5106 (25ms) - EOT: False

Chinese Performance

Sample: "你好，你好吗？" (Hello, how are you?)
  • Namo Multilingual:     0.6525 (30ms) - EOT: False
  • Namo Chinese-Specific: 0.8777 (16ms) - EOT: True ⭐
  • LiveKit Multilingual:  0.8520 (20ms) - EOT: True

Sample: "今天天气怎么样？" (What's the weather today?)
  • Namo Multilingual:     0.6818 (18ms) - EOT: False
  • Namo Chinese-Specific: 0.9090 (34ms) - EOT: True ⭐
  • LiveKit Multilingual:  0.9707 (20ms) - EOT: True

Key Insights:

• Language-Specific models show superior accuracy for their target languages
• Namo Multilingual provides consistent performance across all languages
• Inference speed is competitive, typically 10-30ms per prediction
• Vietnamese detection significantly outperforms baseline multilingual model

API Reference

MultilingualModel

MultilingualModel(threshold: float = 0.7)

Methods:

• predict_end_of_turn(chat_ctx, timeout=10.0) -> float - Returns probability (0.0-1.0)
• unlikely_threshold(language) -> float - Get model's threshold for language

LanguageSpecificModel

LanguageSpecificModel(language: str, threshold: float = 0.7)

Parameters:

• language: Language code ("en", "vi", "zh")
• threshold: Detection threshold (0.0-1.0)

Methods: Same as MultilingualModel

• predict_end_of_turn(chat_ctx, timeout=10.0) -> float - Returns probability (0.0-1.0)
• unlikely_threshold(language) -> float - Get model's threshold for language

Pre-download Models

python main.py download-files

Supported Languages

• Multilingual Model (23+ languages): Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, German, Hindi, Indonesian, Italian, Japanese, Korean, Marathi, Norwegian, Polish, Portuguese, Russian, Spanish, Turkish, Ukrainian, Vietnamese

• Language-Specific Models: English (en), Vietnamese (vi), Chinese (zh)

License

Apache-2.0

Credits

• Models: Namo Turn Detector v1 by VideoSDK
• Framework: LiveKit Agents

Citation

@software{namo2025,
  title = {Namo Turn Detector v1: Semantic Turn Detection for Conversational AI},
  author = {VideoSDK Team},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/collections/videosdk-live/namo-turn-detector-v1-68d52c0564d2164e9d17ca97}
}