Cobra: Picovoice's Voice Activity Detection

🚀 Best-in-class Voice AI!

Detect human speech in real time with Cobra Voice Activity Detection.

Voice activity detection (VAD) is a crucial component of many speech processing solutions. VAD detects the presence of a human voice within a stream of audio. Although simple to describe, this is a challenging task in the presence of non-stationary noise.

New to Voice Activity Detection? Read our Complete Guide to Voice Activity to understand how VAD works, common use cases, and implementation strategies.

Picovoice's Cobra Voice Activity Detection delivers production-grade accuracy with the efficiency required for edge deployment. Initially developed as an internal tool for Picovoice's speech processing pipeline, Cobra VAD uses a proprietary neural network trained on thousands of hours of diverse audio conditions.

Today, we are excited to make it publicly available.

What Makes Cobra Voice Activity Detection Different

1. Industry-Leading Accuracy

Cobra VAD outperforms popular alternatives, including WebRTC VAD and Silero VAD. The ROC curve below shows Cobra VAD's superior performance across all threshold settings:

Cobra VAD achieves the largest Area Under Curve (AUC), demonstrating better accuracy at detecting speech while minimizing false alarms. See the open-source VAD engine benchmark in our docs for details.

2. Exceptionally Efficient

Deep learning powered VAD doesn't necessarily mean heavy computation. Cobra VAD proves deep learning powered VADs can have both accuracy and efficiency:

Real-time Factor (RTF) measures the computational time required to process audio. For example, on an Ubuntu machine with an AMD Ryzen 9 5900X CPU:

Silero VAD (Python) measured an RTF of 0.004, which means
- Processing time: 15.4 seconds per hour of audio
- Real-time CPU usage: 0.43%
Cobra VAD (C) measured an RTF of 0.0005, which means
- Processing time: 1.8 seconds per hour of audio
- Real-time CPU usage: 0.05%

While 0.43% CPU usage appears negligible on high-performance hardware, the efficiency gap becomes critical on resource-constrained devices. On Raspberry Pi Zero, the RTF value for Cobra VAD is 0.05 (= 5% of the CPU usage for real-time processing.) In this scenario, the 8.6x difference means Silero VAD uses almost half of the CPU on Raspberry Pi Zero, making it unfit for resource-constrained devices.

This efficiency enables enterprises to deploy Cobra VAD even on resource-constrained devices while achieving industry-leading accuracy.

3. True Cross-Platform Support

Cobra VAD runs consistently across platforms without compromising performance:

Mobile & Embedded:

Support for various Cortex-M microcontrollers and Cortex-A microprocessors is available for enterprise customers.

Desktop & Server:

Web:

Cobra VAD Web Quick Start Guide (runs in all modern browsers)

4. Probability Scores for Fine-Tuned Control

Cobra VAD returns probability scores [0, 1] for each audio frame. This gives developers flexibility to:

Set application-specific thresholds
Implement hysteresis for stability
Build custom logic for edge cases
Monitor confidence levels in production

Continuous Improvement

Since launch, we've made significant improvements to Cobra VAD's accuracy through model optimization and expanded training data. Read about our latest VAD accuracy improvements.

For a detailed technical comparison of leading VAD engines, see our 2025 VAD Engine Comparison.

Getting Started with Cobra VAD

Create a free Picovoice Console account to start building with Cobra VAD, leveraging publicly available VAD SDKs. Below is the basic Python implementation guide for Cobra VAD with pvcobra:

import pvcobra

# Get your AccessKey from Picovoice Console for free to replace the placeholder below 
cobra = pvcobra.create(access_key='${ACCESS_KEY}')

# Pass in frames of audio to the .process function 
def get_next_audio_frame():
   pass

while True:
   audio_frame = get_next_audio_frame()
   voice_probability = cobra.process(audio_frame)

# Release resources explicitly when done with Cobra Voice Activity Detection 
cobra.delete()

More SDKs:

See all platforms →

Deploy VAD in Production

Cobra VAD is built for production environments:

Reliable: Battle-tested in commercial applications
Documented: Comprehensive documentation and code examples
Supported: Support available for enterprise deployments
Optimized: Minimal latency and memory footprint

Ready to build? Try Cobra VAD in your browser or create a free Picovoice Console account to get started.

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Introducing Picovoice's SOTA Voice Activity Detection Engine: Cobra