The purpose of this project is to develop an android app that can recognize the sounds of teeth grinding during sleep. The model is pre-trained using a convolutional network with Tensorflow's python api, the code is provided in Bruxism_tensorboard.ipynb, the raw .wav files used for training can be downloaded from the dropbox link. Each .wav file is labeled with 1 second segments of teethgrinding. In addition, a .wav file of sound effects was labeled as non-bruxism sound.
TODO: Describe the installation process
TODO: Write usage instructions
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request :D
TODO: Write history
TODO: Write credits
TODO: Write license readme Tensorphone/Android: contains the code for android phone
Tensorphone/Bruxism_tensorboard.ipynb: tensorflow code for building and training convolutional network.
Tensorphone/Resources: Raw .wav sound of bruxism. Used for training.