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Oracle Drags Its Feet in the JavaScript Trademark Dispute
Oracle seeks to dismiss fraud claims in the JavaScript trademark dispute, delaying the case and avoiding questions about its right to the name.
livekit-plugins-turn-detector
Advanced tools
This plugin introduces end-of-turn detection for LiveKit Agents using a custom open-weight model to determine when a user has finished speaking.
Traditional voice agents use VAD (voice activity detection) for end-of-turn detection. However, VAD models lack language understanding, often causing false positives where the agent interrupts the user before they finish speaking.
By leveraging a language model specifically trained for this task, this plugin offers a more accurate and robust method for detecting end-of-turns. The current version supports English only and should not be used when targeting other languages.
pip install livekit-plugins-turn-detector
This plugin is designed to be used with the VoicePipelineAgent
:
from livekit.plugins import turn_detector
agent = VoicePipelineAgent(
...
turn_detector=turn_detector.EOUModel(),
)
This plugin requires model files. Before starting your agent for the first time, or when building Docker images for deployment, run the following command to download the model files:
python my_agent.py download-files
The end-of-turn model is optimized to run on CPUs with modest system requirements. It is designed to run on the same server hosting your agents. On a 4-core server instance, it completes inference in ~50ms with minimal CPU usage.
The model requires 1.5GB of RAM and runs within a shared inference server, supporting multiple concurrent sessions.
We are working to reduce the CPU and memory requirements in future releases.
The plugin source code is licensed under the Apache-2.0 license.
The end-of-turn model is licensed under the LiveKit Model License.
FAQs
End of utterance detection for LiveKit Agents
We found that livekit-plugins-turn-detector demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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