TEN VAD Open-Source Release: A Leap in Voice Detection Tech

The TEN Agent team has announced the open-source release of its enterprise-level real-time voice activity detector (TEN VAD), a move that has sparked widespread discussion in the tech industry. With frame-level accuracy in voice detection, TEN VAD outperforms existing solutions like WebRTC VAD and Silero VAD, positioning itself as a powerful engine for building real-time dialogue voice assistants.

Enterprise-Level Voice Detection with Frame-Level Precision

TEN VAD is a lightweight, low-latency voice activity detection model based on deep learning. Designed for enterprise applications, it accurately identifies human speech in audio frames while filtering out background noise and silence. In diverse scenario tests, TEN VAD demonstrates higher accuracy and lower false alarm rates, particularly excelling in complex noise environments. Its frame-level detection ensures rapid identification of transitions between speech and non-speech, crucial for real-time dialogue systems.

Low Latency and High Compatibility: Cross-Platform Deployment

TEN VAD stands out not only for its performance but also for its low computational complexity and small memory footprint. Compared to Silero VAD, it reduces the real-time factor (RTF) by approximately 32%, offering lower latency across various hardware platforms. Additionally, TEN VAD supports the ONNX model format and is compatible with five major operating systems: Linux, Windows, macOS, Android, and iOS. It also provides support for Python and WebAssembly (WASM), enabling easy deployment on any ONNX-compatible platform or web application.

Collaboration with TEN Turn Detection: Natural Dialogue Experience

The integration of TEN VAD and TEN Turn Detection opens new possibilities for creating human-like voice assistants. TEN Turn Detection is an intelligent turn-taking model designed for full-duplex voice communication, capturing pauses and intonation cues to enable context-aware interruptions and responses. This combination allows AI voice assistants to achieve near-human levels of conversation fluency and real-time performance, enhancing user experience in applications like smart customer service and interactive devices.

Open Source Empowerment: Accelerating Voice AI Innovation

The open-source release of TEN VAD marks a new phase in voice AI technology. Since its launch, the GitHub repository has garnered over 600 stars, reflecting strong developer interest. The project includes pre-trained models and related preprocessing code, allowing developers to customize and optimize as needed. The TEN Agent team has also integrated it into the TEN Framework, simplifying the development of powerful voice AI applications.

Industry Outlook: Redefining Voice Interaction

The release of TEN VAD not only improves voice detection accuracy but also reduces computing costs by minimizing invalid data in speech-to-text (STT) processing. This is particularly impactful for cost-sensitive applications like smart homes and in-vehicle systems. As voice AI expands into customer service, education, and healthcare, TEN VAD’s open-source nature and high performance will drive more natural and intelligent interaction experiences.

Key Points:

• Frame-level accuracy: Superior performance in diverse scenarios.
• Low latency: 32% reduction in RTF compared to Silero VAD.
• Cross-platform support: Compatible with major OSes and programming languages.
• Open-source: Encourages community-driven innovation.
• Cost-effective: Reduces STT processing costs significantly.

Project Address: https://github.com/ten-framework/ten-vad