numpy, tensorflow, libROSA, matplotlib
- dataset_utils.py
Dataset related utilities: One-hot encoding, wav file normalisation, TRS to CSV conversion, JSON to CSV conversion, Youtube wav download for the AudioSet Google corpus, Liblinear library data transformations
- metrics_utils.py
(NOT FINALISED) Metrics' related utilities for the baseline VAD methods
- feature_extractor.py
Feature extraction class to extract MFCC, deltas, double deltas, RSE
- VAD_model.py
LSTM-RNN tensorflow learning model
- _main_.py
The program's main entry point
- /checkpoint
Tensorflow checkpoint directory for saving and restoring learning models
- /parameter
LSTM-RNN learning model hyper-parameters, training parameters, and log/checkpoint directories names
- /notebook
Jupyter notebooks to test initial VAD prototypes