TEN VAD - Voice Activity Detector

TEN VAD is a lightweight, high-performance Voice Activity Detector (VAD) designed for real-time speech detection with superior accuracy and minimal computational overhead.

Overview

TEN VAD delivers exceptional precision compared to industry alternatives like WebRTC VAD and Silero VAD, while consuming significantly fewer computational resources and memory.

Key Performance Metrics:

• Real-Time Factor: 0.015 on AMD Ryzen (exceptionally fast)
• Library Size: Only 306KB (minimal footprint)
• Superior precision compared to WebRTC and Silero VAD
• Frame-level speech activity detection for fine-grained control

Features

Multi-Platform Support

• Desktop: Linux, Windows, macOS
• Mobile: Android, iOS
• Web: Browser integration via WebAssembly

Multi-Language Bindings

Build VAD detection in your preferred language:

• Python (with numpy)
• C/C++
• Java (with JNI support for Android)
• Go
• JavaScript/WebAssembly

Technology Stack

• ONNX Model Format for cross-platform deployment and optimization
• WebAssembly Support for seamless browser integration
• JNI Bindings for native Android support

Use Cases

• Real-time Voice Assistants — Detect speech onset and offset for responsive interaction
• Voice Conferencing — Identify active speakers in multi-party conversations
• Speech Recognition Preprocessing — Optimize ASR pipeline by filtering silence
• Mobile Applications — Lightweight detection on resource-constrained devices
• Browser-Based Applications — Client-side speech detection without server round-trips

Performance Highlights

TEN VAD outperforms comparable alternatives across diverse hardware platforms:

• Minimal computational complexity
• Reduced memory usage
• Fast inference time (Real-Time Factor < 1)
• Accurate frame-level detection

This makes it ideal for:

• Edge deployment scenarios
• Real-time conversational AI
• Mobile and web applications
• Multi-stream processing

Getting Started

Installation

# Python
pip install ten-vad

# JavaScript/Node.js
npm install ten-vad

Basic Usage

from ten_vad import VAD

# Initialize VAD
vad = VAD()

# Process audio frames
for frame in audio_stream:
    is_speech = vad.detect(frame)
    if is_speech:
        print("Speech detected!")

Integration with TEN Agent

TEN VAD is a core component of TEN Agent's speech processing pipeline:

• Enables natural interruption handling in voice interactions
• Improves responsiveness by detecting speech boundaries
• Reduces unnecessary processing of silence

Use TEN VAD with the TEN framework for:

• Voice Activity Detection — Identify when users are speaking
• Turn Detection — Combined with TEN Turn Detection for intelligent conversation flow
• Barge-in Support — Enable users to interrupt AI responses naturally

Resources

• GitHub Repository: TEN-framework/ten-vad
• Documentation: Full API reference and examples
• Community: 1.6k stars, 131 forks, active Discord and WeChat communities

Latest Updates (2025)

Recent releases include:

• Python inference with ONNX models on Linux and macOS
• Full Golang support across major operating systems
• Java support on multiple platforms including Android
• Enhanced model accuracy and performance optimizations

License

TEN VAD is open-source and community-driven. Check the repository for licensing details.