OpenBCI data processing for subvocal recognition

This is the repo to turn OpenBCI raw data into spectrograms and to train the model on said data.

`1_openbci_to_wavfile.ipynb`

Checks the latest recordings in the SavedData folder from OpenBCI, takes the array of values of each channel
and turns it into a wavfile.

`2_wav_to_spectrogram.ipynb`

Before executing this code you first need to split the data using the process_audio.py from subvocalization_stream,
once you split the wavfiles, this code transforms the individual wavfiles into sepctrograms.

`3_spectrogram_to_csv.ipynb`

This script will get the file location of each spectrogram and list them into a csv file for training the model.

`4_subvocal_train_model.ipynb`

This script will train the model using the assigned csv file.

`5_subvocal_model_find_outliers.ipynb`

Using the trained model we can apply it to the dataset to find outliers and create a csv file to exclude said outlier data.