Audio events classifier
- create_train_set.ipynb - creates and saves training set with 13 MFCC features for each time window (standard size is 25 ms and step is 10 ms, see python_speech_features documentation) in each file. All the files that are longer than 6 seconds are split to the 6 seconds subfiles and files shorter than 6 seconds are padded with zeros in the end.
- train_model.ipynb - loads training set, builds and fits Bidirectional LSTM model with 80 hidden units, saves the model.
- prepare_test_set_and_predict.ipynb - creates the testing set in the same way as the training set is done, loads saved model and predicts values for the testing set, saves the result to the
result.txt. - draft_create_train_set_and_bidir_LSTM.ipynb - file is used for testing the ideas on the small amount of data.
- Install python_speech_features library by running
pip install python_speech_features
- Clone this git repository to the same folder as data_v_7_stc
- Run in the next order 3 notebooks one by one:
- create_train_set.ipynb
- train_model.ipynb
- prepare_test_set_and_predict.ipynb
- Results will be saved in the text file
result.txt
- python 3.6.3
- cython 0.28.3
- ipython 6.4.0
- jupyter 1.0.0
- h5py 2.8.0
- keras 2.2.0
- matplotlib 2.2.2
- numpy 1.12.1
- pandas 0.23.1
- pip 10.0.1
- python-speech-features 0.6
- scipy 1.1.0
- tensorflow 1.8.0