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Auralisation of learned features in CNN (for audio)


This repo is for an example of auralisastion of CNNs that is demonstrated on ISMIR 2015.

Files

auralise.py: includes all required function for deconvolution. example.py: includes the whole code – just clone and run it by python example.py You might need to use older version of Keras, e.g. this (ver 0.3.x)

Folders

src_songs: includes three songs that I used in my blog posting.

Usage

Load weights that you want to auralise. I’m using this function W = load_weights() to load my keras model, it can be anything else. W is a list of weights for the convnet. (TODO: more details)

Then load source files, get STFT of it. I’m using librosa.

Then deconve it with get_deconve_mask.

Citation

This paper, or simply,

@inproceedings{choi2015auralisation,
  title={Auralisation of Deep Convolutional Neural Networks: Listening to Learned Features},
  author={Choi, Keunwoo and Kim, Jeonghee and Fazekas, George and Sandler, Mark},
  booktitle={International Society of Music Information Retrieval (ISMIR), Late-Breaking/Demo Session, New York, USA},
  year={2015},
  organization={International Society of Music Information Retrieval}
}

External links

Credits

GitHub

https://github.com/keunwoochoi/Auralisation


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