By distilling a general-purpose audio foundation model, researchers created a practical denoiser for animal recordings that's both faster and more effective than specialized bioacoustic methods, showing that foundation models can be efficiently adapted for domain-specific audio tasks.
CallCleaner is a lightweight audio denoising tool for animal recordings that distills a large foundation model into a 19M-parameter neural network. It removes background noise from field recordings of animal vocalizations without requiring voice detection, runs 90x faster than real-time on a laptop CPU, and outperforms existing bioacoustic denoisers while maintaining call quality.