jonnor/machinehearing
Machine Learning applied to sound
Focuses on audio event detection, anomaly detection, and acoustic classification tasks using spectrogram-based feature extraction and CNNs deployable on microcontrollers. Emphasizes edge ML solutions with compressed spectrograms for privacy-preserving cloud inference, supported by practical Python implementations using librosa and Keras for real-time sound sensing applications.
288 stars. No commits in the last 6 months.
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Last pushed
Jun 08, 2025
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