Recently, the TEN Agent team announced the official open-source release of its enterprise-level real-time voice activity detector (TEN VAD), a groundbreaking move that has sparked widespread industry discussion. With frame-level accuracy in voice detection and performance superior to WebRTC VAD and Silero VAD, TEN VAD has become a powerful engine for building real-time dialogue voice assistants.
TEN VAD: Enterprise-Level Voice Detection with Frame-Level Precision
TEN VAD is a lightweight, low-latency voice activity detection (VAD) model based on deep learning, specifically designed for enterprise applications. It can accurately identify human speech in audio frames and filter out background noise, silence, and other non-speech content. Compared to widely used industry solutions like WebRTC VAD and Silero VAD, TEN VAD demonstrates higher accuracy and lower false alarm rates in diverse scenario tests, especially excelling in complex noise environments. Its frame-level detection capability ensures rapid identification of transitions between speech and non-speech, providing a solid foundation for real-time dialogue systems.
Low Latency and High Compatibility: A Powerful Tool for Cross-Platform Deployment
TEN VAD not only leads in performance but is also known for its low computational complexity and small memory footprint. Compared to Silero VAD, TEN VAD reduces the real-time factor (RTF) by approximately 32%, showing lower latency across various hardware platforms. Additionally, TEN VAD supports the ONNX model format, is compatible with five major operating systems—Linux, Windows, macOS, Android, and iOS—and provides support for Python and WebAssembly (WASM). Developers can easily deploy it on any ONNX-compatible platform or web application. This cross-platform flexibility greatly lowers the development barrier and paves the way for the popularization of voice AI.
Collaboration with TEN Turn Detection: Creating a Natural Dialogue Experience
The combination of TEN VAD and TEN Turn Detection opens up new possibilities for building human-like voice assistants. TEN Turn Detection is an intelligent turn-taking detection model specifically designed for full-duplex voice communication, capable of capturing pauses, intonation, and other cues in natural conversations to enable context-aware intelligent interruptions and responses. This integration allows AI voice assistants to approach human interaction levels in terms of conversation fluency and real-time performance, significantly enhancing user experience. Whether in smart customer service, virtual assistants, or interactive devices, the collaborative application of TEN VAD and TEN Turn Detection demonstrates unparalleled potential.
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 quickly gained over 600 stars, reflecting strong interest from the developer community. TEN VAD not only provides pre-trained models but also opens up related preprocessing code, allowing developers to customize and optimize according to their needs. Furthermore, the TEN Agent team has integrated it into the TEN Framework, enabling developers to build powerful voice AI applications with simple configuration. AIbase believes that the open-source nature of TEN VAD will greatly promote innovation in voice interaction technology, injecting new vitality into fields such as smart devices, the Internet of Things, and real-time communication.
Industry Outlook: Redefining the Future of Voice Interaction
The release of TEN VAD not only improves the accuracy and efficiency of voice detection but also significantly reduces computing costs by minimizing the amount of invalid data in speech-to-text (STT) processing. This is particularly significant for cost-sensitive applications such as smart homes and in-vehicle voice systems. As voice AI is increasingly applied in areas like customer service, education, and healthcare, the open-source and high-performance features of TEN VAD will accelerate the industry's shift toward more natural and intelligent interaction experiences.
AIbase believes that TEN VAD and its supporting technologies will provide developers with endless possibilities, helping voice AI transition from laboratories to households. In the future, as the community continues to contribute, TEN VAD is expected to become a benchmark tool in the field of voice interaction, redefining the boundaries of human-computer dialogue.
Project Address: https://github.com/ten-framework/ten-vad