scholarly journals A Machine Learning Approach to Automatic Music Genre Classification

2008 ◽  
Vol 14 (3) ◽  
pp. 7-18 ◽  
Author(s):  
Carlos N. Silla ◽  
Alessandro L. Koerich ◽  
Celso A. A. Kaestner
2008 ◽  
Vol 14 (3) ◽  
pp. 7-18 ◽  
Author(s):  
Carlos N. Silla Jr. ◽  
Alessandro L. Koerich ◽  
Celso A. A. Kaestner

Author(s):  
Ashfaqur Rahman

Bangladesh is very rich in its musical history. Music documented the lives of the people from the ancient times. This chapter provides a guideline for classifying Bangla songs into different genres using a machine learning approach. Four different genres, namely Rabindrasangit, Folk song, Adhunik song, and Pop music, were used in the experiments. A set of second order features are used for representing the trend of change of primary features computed over the timeline of the song. The features are incorporated into a number of classification algorithms and a classification framework is developed. The uniqueness of the genres is clearly revealed by high classification accuracies achieved by the different classifiers.


Author(s):  
Mekala Srinivasa Rao ◽  
O. Pavan Kalyan ◽  
N. Naresh Kumar ◽  
Md. Tasleem Tabassum ◽  
B. Srihari

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