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Verified signature--- license: mit language: - id - en tags: - audio-classification - heart-sound - medical - cnn-lstm - health pipeline_tag: audio-classification --- # SIRAJA Heart Sound Classifier **CNN-LSTM model for heart sound classification** · 98.3% accuracy Classifies heart sounds into three categories: Normal, Murmur, or Artifact. --- ## 🎯 Model Description SIRAJA is a hybrid CNN-LSTM deep learning model trained to classify heart sounds from auscultation recordings. The model analyzes MFCC features extracted from audio signals to detect: - **Normal** — Regular heart rhythm with clear S1/S2 sounds - **Murmur** — Turbulent blood flow indicating potential valve issues - **Artifact** — Noise/interference in the recording --- ## 📊 Performance | Metric | Score | |--------|-------| | Test Accuracy | **98.30%** | | Validation Accuracy | **98.86%** | **Per-Class Results:** | Class | Precision | Recall | F1-Score | |-------|-----------|--------|----------| | Artifact | 100.00% | 100.00% | 1…33243d3 -
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