https://github.com/zivl/nlp_final

final nlp project at IDC 2013 - by Ziv and Shachar
https://github.com/zivl/nlp_final

Last synced: about 1 year ago
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final nlp project at IDC 2013 - by Ziv and Shachar

• Host: GitHub
• URL: https://github.com/zivl/nlp_final
• Owner: zivl
• Created: 2013-05-30T14:56:02.000Z (about 13 years ago)
• Default Branch: master
• Last Pushed: 2013-07-07T07:23:57.000Z (almost 13 years ago)
• Last Synced: 2025-03-14T21:04:51.189Z (about 1 year ago)
• Language: Java
• Size: 1.92 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
NLP@IDC – Final Course Project, Spring 2013


Songs Genres Classification








Today, we usually define a song’s genre by its vocal elemnts – melody, instruments, etc.

We intend to find if we can define a genre simply through the lyrics – whether the written elements of songs contain significant genre information. 


Why ?

Because its AWESOME!



	Also, this is important to the study of literature and poetry – it could hint at a cognitive connection between melodies and ideas, and help us define the term “genre” and its meanings, thus grounding the study of literature and poetry in something a bit more robust than just personal taste and opinion. 



How? Logistic Regression

Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables. 





Variables



	
Words – we’ll examine how distinct is the vocabulary of each genre.

	
Structure – if time constraints will allow, we’ll examine whether genres also imply a certain structure on the lyrics.

	
Diversity – even if genres use the same words, do they repeat themselves (“Baby, baby, baby oooh”), or does each song contain a wider selection of words?



Limitations and Future Enhancements

Lyrics databases aren’t quality-controlled, don’t carry the same formats between songs (especially obvious with “censored” words, which can be written in different ways – S-it, Sh*t, *%#$, etc.)

No existing tree-banks on song lyrics, which limits us to low-level analysis.

No efficient data-mining tools – either we create them, or we hand-create all of our data-sets.