Detect the presence of human voice activity in audio streams
Accurate, lightweight, and production-ready VAD
Start Building for FreeTalk to SalesCheck out the open-source benchmark that indicates Cobra VAD outperforms Google’s well-known WebRTC VAD with wide margins. Cobra VAD achieves a much higher true-positive rate at any false-positive operating point.
Cobra VAD runs even on microcontrollers or even offline within your browser. After starting the demo, turn off your internet. It keeps working, right?
Start BuildingBuild voice-activated experiences with the SDK of your choice. Cobra VAD supports Python, Android, iOS, JavaScript, Rust, and C.
o = pvcobra.create(access_key)while True:is_voiced =o.process(audio_frame())Build with Python
Cobra o = new Cobra(accessKey);while(true) {float isVoiced =o.process(audioFrame());}Build with Android
let o =Cobra(accessKey: accessKey)while true {let isVoiced =o.process(audioFrame())}Build with iOS
let o =await CobraWorker.create(accessKey,(isVoiced) => {// callback})const processor =WebVoiceProcessor.instance()processor.subscribe(o)await processor.start()Build with JavaScript
let o = Cobra::new(access_key).expect("");loop {let is_voiced = o.process(&audio_frame()).unwrap();}Build with Rust
pv_cobra_init(access_key,&cobra);while (true) {pv_cobra_process(cobra,audio_frame(),&is_voiced);}Build with C
Add voice activity detection to your existing platforms. Expand later without worrying about the support. Cobra VAD runs on web browsers, mobile platforms, single board computers, microcontrollers, on-premise, or even in the cloud.
Start BuildingAdd voice for truly hands-free search experiences on the websites, mobile applications and devices.
Search By VoiceAdd voice search to mobile applications, websites, and devices. Find keywords and phrases in audio, video, and streams.
Voice SearchTransformative customer and employee experience with speech analytics and intelligence tools powered by the only end-to-end Voice AI platform.
Speech AnalyticsAdd voice commands to devices, mobile or web applications to elevate user experience.
Voice CommandVoice activity detection (VAD) is a technology used to detect the presence of human speech within an audio signal containing speech and noise. That is why it is also known as speech activity detection, speech detection, or voice detection. VAD is essential to enable automatic speech recognition (ASR). We initially developed Cobra as an internal tool and then made it publicly available since no computationally efficient and accurate VAD was available.
Typical VAD methods use learned statistical models such as the Gaussian mixture model, just like the most popular WebRTC VAD. WebRTC VAD is good, computationally efficient and works for streaming audio signals. On the other hand, Cobra VAD uses deep learning. Cobra’s proprietary algorithm is developed by applying Picovoice’s expertise in on-device voice recognition. Therefore, Cobra VAD could achieve higher accuracy and run across platforms.
Cobra VAD processes voice data on-device, resulting in private, HIPAA and GDPR compliant experiences. The data could be processed within a web browser, on a mobile application, in an IoT device, a laptop or a server. On your terms!
Cobra VAD can be used alone or paired with other engines, Rhino Speech-to-Intent and Leopard Speech-to-Text for several use cases such as call-centre automation, telemarketing, audio conferencing, filtering, voice assistants and so on. Don’t forget to check out Voice Command and Control, Search by Voice and Speech Analytics use cases to learn more about various voice AI applications with Cobra VAD.
Picovoice docs, blog, Medium posts, and GitHub are great resources to learn about voice recognition, Picovoice engines, and how to start building voice-activated products. Picovoice also offers GitHub community support to all Free Tier users.
Version changes appear in the Picovoice Newsletter, LinkedIn, and Twitter. Subscribing to GitHub is the best way to get notified of the patch releases. If you enjoy building with Cobra, don’t forget to give it a star when you’re on GitHub!