BabbleLabs uses speech science and AI to remove noise and enhance voices in real-time communications and recordings.
BabbleLabs built its reputation on Clear Voice, speech enhancement technology that removes background noise while preserving natural voice quality. Its deep learning models separate speech from noise, babble and reverberation in real time — making it valuable for conferencing products, hearing devices and enterprise communications. SDK and licensing options let product teams embed enhancement directly, and the company’s research roots show in the naturalness of processed speech.
BabbleLabs technology is licensed to businesses through evaluation and commercial agreements; pricing depends on deployment.
Communications and audio product teams that want best-in-class speech enhancement embedded in their platforms.
Conferencing vendors embed Clear Voice to clean participant audio, and hearing technology companies use the models to improve speech intelligibility in noisy environments.
Contact the team for evaluation SDKs, integrate the enhancement into your audio pipeline and benchmark against your current noise handling.
It is licensed technology; evaluation access is arranged with the company.
SDKs and embedded processing are the integration model rather than a cloud API.
Versus consumer tools like Krisp, BabbleLabs targets embedded and professional scenarios with research-grade speech models.
The models are designed to preserve voice naturalness while removing noise — a research priority that differentiates earlier suppression techniques.
Optimized models run in real time on typical device and server hardware; specifics depend on the deployment target.
Noisy homes, cafés and offices — the conditions that made remote work audio infamous — are exactly where its speech separation shines.
BabbleLabs targets embedded and professional licensing with research-grade models, while Krisp sells direct-to-consumer and prosumer desktop tools.
Yes — removing competing voices and background chatter is one of the model’s core specializations beyond simple steady-state noise.
Communications platforms, device makers and enterprise product teams embed the models through evaluation and commercial licensing agreements.