< Overview >
An AI project that can help in the classification of sounds which can be used for crime scene investigations.
- The MLP (Multi Layer Perceptron) and Random Forest model has been used for the comparison to see which performs better
- UrbanSound8k dataset composed of 8732 tagged sound clips with a duration of less than or equal to 4 seconds were used to train the model
- Libra which helps in audio analysis with MFCC was being used for feature extraction
- MLP model performs best with an accuracy of 92.73 %, whereas RF model performs best with an accuracy of 61.11 %, indicating that MLP performs better than RF on audio or time series data.
- The model has been saved in .h5 (1.3 MB) and.joblib (150.6 MB) formats for MLP and RF respectively.