ABSTRACT PROPOSAL:
Project Id and title:
- Team Number: 41
- Project Id: 12
- Team Name: Slow and Steady
- Project Title: Music Genre Classification from Lyrics
Github link: https://github.com/Animireddy/SMAI_PROJECT_12.git
Team Members:
- Animi Reddy 20161191
- Sri Keshav 20161023
- Sushman 20161143
- Raghuchandra 20161305
Main goal(s) of the project:
- Music Genre Classification from Lyrics
Problem definition (What is the problem? How things will be done?):
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Problem is Music Genre Classification from Lyrics
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We do it by the following way:
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Read train data from input.csv file
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csv file contains 2 columns - genre and song
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Creating Word vectors
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Convert all collected songs from input.csv to a matrix of token counts
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This can be done by using inbuilt CountVectorizer() function from sklearn.
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Matrix order: (No.of Songs in input.csv)*(Total No.of distinct Words)
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Give this matrix as input to Training model(like SVM) along with corresponding genre output matrix.
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Finally done with train model.
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Results of the project:
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We do following steps for a given testfile
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Convert all collected songs from testfile to a matrix of token counts
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This can be done by using inbuilt CountVectorizer() function from sklearn.
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Matrix order: (No.of Songs in testfile)*(Total No.of distinct Words)
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Call for predict function in train model and get the predicted output.
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With original output and predicted output we can find the accuracy obtained with the model.
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Team members and tasks for each member:
- Not yet decided.
Project milestones and expected timeline:
Task Expected time
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Collecting train and test data from online sources. 18-03-2019
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Build a model for the problem Not yet decided(may be last week of march or first week of April)
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Run on test data Not yet decided