This project creates embeddings of song lyrics with Doc2Vec, reduces the resulting dimensionality with t-SNE, and compares artist-by-artist song clusters.
A full description of the project can be found at saisenberg.com.
- Python
- Python:
contractions, collections, gensim, nltk, pandas, re, sklearn, string (```install any missing libraries with !pip install [library name]```)
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Change paths in params.py as appropriate.
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Update artist dictionary in params.py as appropriate.
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Change working directory in run.py as appropriate, and run entire file. Note that additional parameters are available for many LyricsAnalyzer methods; see LyricsAnalyzer.py for further details on available options.
- Sam Isenberg - saisenberg.com | github.com/saisenberg
This project is licensed under the MIT License - see the LICENSE.md file for details.