Tunçer D, Barçin K, Bölücü N, Erdem A. Music Genre Recognition with Machine Learning. Poster presented at 27th Signal Processing and Communications Applications Conference (SIU), Sivas, 2019.
In order to run
- Support Vector Machines
support_vector_machines.pyorsupport_vector_machines.ipynb - Nearest Neighbors
nearest_neighbors.pyornearest_neighbors.ipynb - Logistic Regression
logistic_regression.pyorlogistic_regression.ipynb - Neural Network
nn.pyornn.ipynb
extract tracks.csv and features.csv from FMA: A Dataset For Music Analysis
You can test your audio on: application.ipynb
- Video Presentation: rock or not?
- Project Presentation:
rock_or_not_presentation.pptx - Progress Report:
progress_report.pdf - Final Report:
final_report.pdf
Medium Blogs:
- Week 1 Introduction
- Week 2 Dataset Exploration
- Week 3 Dataset Exploration (Continued)
- Week 4 Related Works
- Week 5 Methods
- Week 6 Methods (Continued)
- Week 7 Results and Conclusion
Course Page: BBM406-Fall2018
REFERENCES