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Poisson matrix factorization and automatic music tagging

Source code for the paper: Codebook-based Scalable Music Tagging with Poisson Matrix Factorization by Dawen Liang, John Paisley and Dan Ellis, in ISMIR 2014.

Dawen Liang dliang@ee.columbia.edu

(C) Copyright 2014, Dawen Liang

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

What's included:

There are four ipython notebook files, which will help reproduce the experiments in the aforementioned paper:

  • buildVQ_MSD.ipynb: Build the VQ Codebook for the Million Song Dataset and vector-quantize the MSD and save to disk.

  • processLastfmTags.ipynb: Process the tagging data from Last.fm and build the vocabulary and bag-of-tags representation and save to disk.

  • tagging_ooc.ipynb: After building the VQ-histogram and bag-of-tags, this one will reproduce the results from the data saved on the disk.

  • tagging_in_memory.ipynb: If you have enough memory, you can also save the data from tagging_ooc.ipynb and directly fit to the PMF with this notebook.

Dependencies:

  • numpy
  • scipy
  • scikit-learn (for evaluation metrics)
  • nltk (for tag stemming)

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