Hance.ai

HANCE AI: Realtime AI Audio Enhancement is an embedded, real-time audio enhancement solution designed for manufacturers and developers of audio hardware and software. It delivers ultra-fast AI-powered audio processing (as fast as 10 milliseconds per operation) that can be integrated into a wide range of devices and software to remove noise, suppress reverb, boost voices, and separate stems from music. Designed for low CPU/memory usage, it enables high-quality audio enhancement directly on end devices without cloud processing.

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How it works

• Real-time audio processing with lightweight models (as small as 242 KB up to a few MB) that run locally on hardware or in software.
• Core capabilities include Noise Removal, Echo/Room Reverb Removal, and Stem Separation for separating vocals, piano, bass, and drums in music.
• Highly codified, trainable, and adaptable AI models tailored for consumer electronics, professional audio software, hearing aids, conferencing, and streaming applications.
• Designed for easy integration with minimal R&D burden, enabling customization to fit specific product needs.

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Use Cases

• Voice communication and conferencing with clearer speech.
• Hearing aid and assistive listening devices.
• Music production and live performance software requiring real-time stem separation.
• Consumer electronics and hardware with embedded AI audio enhancement.

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How to Use HANCE (Overview)

1. Assess your hardware/software requirements and choose the appropriate HANCE model size.
2. Integrate the HANCE API into your product (API available for C++ and Python; more languages planned).
3. Configure noise suppression, reverb removal, voice enhancement, and stem separation to fit your use case.
4. Deploy on target devices and test in real-time scenarios; monitor CPU/memory usage and audio quality.

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API & Integration

• Lightweight, CPU-efficient embedded AI audio engine.
• API documentation and support available for rapid integration.
• Customizable AI models to match specific hardware capabilities and deployment needs.
• On-device processing ensures data privacy and reduces latency.

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Safety & Privacy Considerations

• On-device processing minimizes data transmission, enhancing privacy.
• Properly configure models to avoid unintended data capture or eavesdropping risks.
• Ensure compliance with relevant data protection regulations when handling voice data in products.

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Core Features

• Real-time AI audio enhancement with processing speeds down to 10 ms
• Noise Removal for clearer voice communication
• Echo/Room Reverb Removal for improved intelligibility
• Stem Separation (vocals, piano, bass, drums) for music applications
• Ultra-lightweight model sizes (as small as 242 KB; library up to ~5 MB)
• Low CPU and memory footprint suitable for embedded deployment
• Customizable AI models to fit hardware and software needs
• Easy integration with C++ and Python APIs (more languages planned)
• On-device processing with strong privacy benefits