Ditch the Cloud: Building a Privacy-First Sleep Apnea Detector with Whisper.cpp and TFLite πŸŒ™πŸ’€

Have you ever been told you "snore like a freight train"? Or worse, do you wake up feeling like you’ve run a marathon in your sleep? You might be dealing with sleep apnea, a condition where breathi...

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Ditch the Cloud: Building a Privacy-First Sleep Apnea Detector with Whisper.cpp and TFLite πŸŒ™πŸ’€

Source: DEV Community

Have you ever been told you "snore like a freight train"? Or worse, do you wake up feeling like you’ve run a marathon in your sleep? You might be dealing with sleep apnea, a condition where breathing repeatedly stops and starts. While there are apps for this, most of them ship your private bedroom audio to a distant server for analysis. That’s a massive "no-thank-you" for privacy! Today, we are building Sleep-Ops: a real-time, edge-computing solution for sleep apnea detection using Whisper.cpp and TensorFlow Lite. We’re keeping the data where it belongsβ€”on your device. By the end of this guide, you’ll understand how to implement real-time audio processing, leverage edge AI, and master spectrogram-based classification. The Architecture: Why "Edge" Matters πŸ›‘οΈ The secret sauce here is the hybrid approach. We use Whisper.cpp for robust voice activity detection (VAD) and segmenting audio, while a lightweight CNN (Convolutional Neural Network) handles the heavy lifting of identifying specif

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