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https://github.com/rasbt/musicmood

A machine learning approach to classify songs by mood.
https://github.com/rasbt/musicmood

exploratory-data-analysis lyrics machine-learning mood song-dataset

Last synced: 13 days ago
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A machine learning approach to classify songs by mood.

Host: GitHub
URL: https://github.com/rasbt/musicmood
Owner: rasbt
License: gpl-3.0
Created: 2014-12-07T19:20:40.000Z (almost 10 years ago)
Default Branch: master
Last Pushed: 2016-11-02T00:23:40.000Z (about 8 years ago)
Last Synced: 2024-10-03T10:12:21.231Z (about 1 month ago)
Topics: exploratory-data-analysis, lyrics, machine-learning, mood, song-dataset
Language: OpenEdge ABL
Size: 53.3 MB
Stars: 412
Watchers: 33
Forks: 108
Open Issues: 5
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # MusicMood

### A machine learning approach to classify music by mood based on song lyrics.

This project is about building a music recommendation system for users who want to listen to *happy* songs. Such a system can not only be used to brighten up one's mood on a rainy weekend; especially in hospitals, other medical clinics, or public locations such as restaurants, the MusicMood classifier could be used to spread positive mood among people.




### Links

- [The web application](http://rasbt.pythonanywhere.com)

- [The data collection IPython notebook](code/collect_data/data_collection.ipynb)

- [The initial model training IPython notebook](code/classify_lyrics/nb_init_model.ipynb)

- [The updated model training with white lists IPython notebook](code/classify_lyrics/nb_whitelist_model.ipynb)

- [Experiments with Random Forests IPython notebook](code/classify_lyrics/random_forests.ipynb)

- [An article about my experiences with this project](http://sebastianraschka.com/blog/2014/musicmood.html)

- [A keynote presentation about this project](https://speakerdeck.com/rasbt/musicmood-machine-learning-in-automatic-music-mood-prediction-based-on-song-lyrics)

- [A more technical report on arXiv](https://arxiv.org/abs/1611.00138)







### Sections



- [Dataset Summary](#dataset-summary)

- [Exploratory Data Analysis](#exploratory-data-analysis)

- [Results](#results)









![](./images/flowchart.png)







## Dataset Summary

[back to top](#sections)

- A 10,000-song subset was downloaded from the [Million Song Dataset](http://labrosa.ee.columbia.edu/millionsong/pages/getting-dataset).

- Lyrics were automatically downloaded from [LyricWikia](http://lyrics.wikia.com/Lyrics_Wiki) and all songs for which lyrics have not been available were removed from the dataset.

 - An English language filter was applied to detect and remove all non-English songs.

 -  The remaining songs were randomly subsampled into a 1000-song training dataset and 200-song validation dataset.







## Exploratory Data Analysis

[back to top](#sections)

![](./images/exploratory_1.png)







![](./images/wordclouds.png)







## Results

[back to top](#sections)

![](./images/roc_best.png)

![](./images/performance_table.png)