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README.md
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- Activation: Softmax (to output probabilities for each class).
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- **Model Performance:**
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1. Accuracy and Preprocessing (Table Summary)
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- The CNN model achieves the highest accuracy of 98.37% in the 8th configuration.
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- Key factors contributing to this performance:
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- Library: Keras is used for training and architecture implementation.
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- Sample Rate: A consistent sample rate of 16,000 Hz was maintained for all preprocessing steps.
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2. Confusion Matrix Analysis
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## Model Usage
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- Activation: Softmax (to output probabilities for each class).
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- **Model Performance:**
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1. Accuracy and Preprocessing (Table Summary)
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- The CNN model achieves the highest accuracy of 98.37% in the 8th configuration.
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- Key factors contributing to this performance:
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- Library: Keras is used for training and architecture implementation.
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- Sample Rate: A consistent sample rate of 16,000 Hz was maintained for all preprocessing steps.
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2. Confusion Matrix Analysis
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- High Precision: Minimal false positives suggest the model is very specific when identifying emergencies.
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- High Recall: Minimal false negatives indicate that most emergencies are correctly identified.
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## Model Usage
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