Researchers Fine-Tune OpenAI Whisper to Screen for Sleep Apnea via Audio

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A new AI-driven approach repurposes OpenAI's Whisper speech model as a clinical screening tool for Obstructive Sleep Apnea (OSA), a condition estimated to affect nearly 1 billion people globally. The technique uses fine-tuning via Hugging Face Transformers to train Whisper on non-speech acoustic events such as snoring, normal breathing, and apnea silences rather than conventional speech. Audio preprocessing is handled through the Librosa library, which cleans and segments sleep recordings into 30-second windows before they are passed through Whisper's encoder. A custom classification head then identifies breathing events and calculates an Apnea-Hypopnea Index to generate an OSA risk report. The method aims to make OSA screening more accessible by potentially replacing expensive clinical polysomnography with a standard smartphone recording.

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