Detect human voice activity in real time.
Production-ready voice activity detection, doubling the accuracy of webRTC VAD with deep learning
What is Cobra Voice Activity Detection?
Cobra Voice Activity Detection (VAD) is software that scans audio streams to identify the presence of human speech in real time.
Production-ready Cobra Voice Activity Detection enables adding highly accurate voice detection to any platform in minutes.
Cross-platform Voice Activity Detection with a few lines of code
c = pvcobra.create(access_key)while True:is_voiced =c.process(audio_frame())
Why Cobra Voice Activity Detection?
Cobra Voice Activity Detection is powered by deep learning, whereas alternatives like webRTC VAD use classic signal processing.
Production-ready Cobra Voice Activity Detection offers what developers need: Twice the webRTC VAD accuracy, ease of use, cross-platform SDKs, and enterprise support.
Voice Activity Detection that simply works anywhere
Production-ready, responsive, accurate, and noise-resilient voice activity detection, enabling enterprises to focus on building core features
Other VAD Engines
- 🧳Hand-tuned algorithms
- 🧑🔬Built for experimentation
- 🆘Community-driven Support
Cobra VAD
- 🧠Powered by deep learning
- 👨💻Production-ready
- 📦Enterprise support
Double the accuracy
Ready with a few lines of code
Scale with no limit
Cobra Voice Activity Detection
Embed Cobra Voice Activity Detection into your product in less than 10 minutes.
Start Free- Production-ready model
- Intuitive SDK
- 3 Monthly Active Users
FAQ
Voice activity detection (VAD) is a technology used to detect the presence of human speech within an audio signal. 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).
Enterprises may have different expectations from Voice Activity Detectors. Cobra Voice Activity Detection is the best Voice Activity Detector for those looking for accurate, cross-platform, resource-efficient, and ready-to-deploy VAD.
The typical voice activity detection algorithms, including the most popular WebRTC VAD, use learned statistical models such as the Gaussian mixture model. It’s an old technique. That’s why WebRTC VAD is good, computationally efficient, and works for streaming audio signals but not great. Cobra Voice Activity Detection uses deep learning, achieving the highest accuracy across all platforms.
Cobra Voice Activity Detection processes real-time conversations or recordings on-device, resulting in private, HIPAA, CCPA, and GDPR-compliant experiences. Cobra Voice Activity Detection can run on web browsers, mobile applications, IoT devices, laptops, or servers wherever the data resides.
Cobra Voice Activity Detection works standalone but also pairs up with other engines and enables several use cases. For example, developers combine Cobra Voice Activity Detection with Rhino Speech-to-Intent for QSR drive-thru voice assistants, with Cheetah Streaming Speech-to-Text for real-time agent coaching, or LLM-powered voice assistants, enabling them to start or stop responding depending on whether human speech or silence is detected, and with Leopard Speech-to-Text for cost-effective audio transcription.
Yes! Reach out to the Picovoice Consulting team to get Cobra Voice Activity Detection ported to your platform or a custom voice activity detector trained for you.
Picovoice docs, blog, Medium posts, and GitHub are great resources to learn about voice AI, Picovoice technology, and how to start building voice-activated products. Enterprise customers get dedicated support specific to their applications from Picovoice Product & Engineering teams. While Picovoice customers reach out to their contacts, prospects can also purchase Enterprise Support before committing to any paid plan.