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simple song recommendation system with acoustic feature extraction and machine learning

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Song Recommendation System

System works for mp3 files. It extracts the acoustic features for first and last 30 seconds from files and saves as a csv file. It gives a recommendation for choosen song. Purpose of the system is to give recommendation to users for best crossfade.

Getting Started

if you would like to change the music file, just replace the songs with new ones and run the main.py.you can change csv file name inside of the code as well or you can merge them

Put only your song files under the music directory.

Prerequisites

What things you need to install the software and how to install them

pip install -r requirements.txt

Installing

A step by step series of examples that tell you how to get a development env running

Say what the step will be

Not given

And repeat

Not given

End with an example of getting some data out of the system or using it for a little demo

Running the tests

Not given

Break down into end to end tests

Explain what these tests test and why

Not given

And coding style tests

Explain what these tests test and why

Not given

Deployment

run main.py file and wait until it ends the feaure extraction

python recommend.py music/David_August_-_Epikur_-_Epikur_EP_\(Official_Video\)-Zvi4JYmRXzI.mp3

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

  • Egehan Gunduz - Initial work - egndz

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

Not given

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simple song recommendation system with acoustic feature extraction and machine learning

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