Emotion Based Categorization of Music Using Low Level Features and Agglomerative Clustering

Authors:
R. Sarkar, S. Dutta, A. Roy, S. K. Saha

Venue:
Proc. of NCVPRIPG 2017 (National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics)

Date:
16-19th December, 2017

Abstract:

In this work, we have considered low level time-domain and spectral features extracted from the music signal and applied unsupervised clustering algorithm like K-means and Agglomerative Clustering to cluster the songs into broadly four emotion classes and then use classification for testing accuracy of the predicted classes.

Links:

• Paper (Springer)
• Poster
• Slide