si_mfcc

Preprocessed dataset: https://drive.google.com/drive/folders/13PfYy6lgAen7t1Q4u9gT7Y0WkNKw1uDi

• dataset.npy contains 1440 numpy arrays with 290x13 MFCC features arrays.
• labels.csv contains 1440 rows of speaker's sex and emotion. Row numbers correspond to dataset.npy

How to use

1. Download raw audio dataset from https://zenodo.org/record/1188976#.XPufrogzaUk. We used only audio .wav files.
2. python wav_cut.py to cut audio files to the same length.
3. python wav_to_mfcc.py to extract MFCC features from audio files.
4. python mfcc_to_numpy.py to transform MFCC.npy files into a single DATASET.npy file and labels.csv.
5. python ffnn.py to create the feed forward neural network, fit the model and evaluate.

Steps 1-4 are optional, you can skip to step 5. if you use the prepared dataset from link above.