LiveKit Plugins Turn Detector

A speech endpoint detection plugin for LiveKit agents based on a custom model.

CommonProductProgramming\LiveKit\\Speech Endpoint Detection\

The LiveKit Plugins Turn Detector is a plugin designed for LiveKit Agents that leverages a custom open-weight model to determine when a user has finished speaking, thereby introducing end-to-end speech endpoint detection. Compared to conventional Voice Activity Detection (VAD) models, this plugin utilizes a language model specifically trained for this task, offering a more accurate and robust method for detecting speech endpoints. Currently, it only supports English and is not recommended for other languages.

\• Provides language model-based speech endpoint detection for improved accuracy and robustness.\
\• Reduces false positives compared to traditional VAD models
preventing the agent from interrupting before the user has finished speaking.\
\• Supports integration with VoicePipelineAgent for developer convenience.\
\• Requires model files
which can be downloaded via command line.\
\• Optimized for CPU execution with moderate system requirements.\
\• Supports multiple concurrent sessions
suitable for operation on an agent server.\
\• Future versions will reduce CPU and memory requirements.\

\The target audience includes developers and enterprises
especially those requiring precise identification of speech endpoints in real-time communication scenarios
such as customer service systems
meeting transcripts
and voice interaction applications. This plugin enhances user experience and boosts service efficiency by reducing false positives and improving detection accuracy.\

\• In an online customer service system
accurately identify when a customer has finished speaking
avoiding premature intervention from automatic replies.\
\• In remote meetings
achieve smoother communication and accurate meeting transcripts through precise detection of speech endpoints.\

\1. Install the plugin: Run the command 'pip install livekit-plugins-turn-detector' in the terminal.\
\2. Integrate the plugin: Import it in your code and configure VoicePipelineAgent to use turn_detector.\
\3. Download the model files: Execute the command 'python my_agent.py download-files' to obtain the necessary model files.\
\4. Start the agent: Launch the configured VoicePipelineAgent to utilize the plugin's features.\
\5. Monitor and adjust: Continuously monitor plugin performance based on actual usage and make adjustments as needed.\

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