Music Mood Visualization Using Self-Organizing Maps

Magdalena Piotrowska; Bożena Kostek

doi:10.1515/aoa-2015-0051

Music Mood Visualization Using Self-Organizing Maps

Abstract

Due to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which music excerpts with similar mood are organized next to each other on the two-dimensional display. Keywords: music mood, music parameterization, MER (Music Emotion Recognition), MIR (Music Information Retrieval), Multidimensional Scaling (MDS), Principal Component Analysis (PCA), Self- Organizing Maps (SOM), ANN (Artificial Neural Networks).

Citations

1 4

CrossRef
0

Web of Science
1 8

Scopus

Authors (2)

Cite as

Full text

download paper

downloaded 50 times

Publication version: Accepted or Published Version
DOI:: Digital Object Identifier (open in new tab) 10.1515/aoa-2015-0051
License: open in new tab

Keywords

Details

Category:: Articles
Type:: artykuł w czasopiśmie wyróżnionym w JCR
Published in:: Archives of Acoustics no. 40, pages 513 - 525,
ISSN: 0137-5075
Language:: English
Publication year:: 2015
Bibliographic description:: Piotrowska M., Kostek B.: Music Mood Visualization Using Self-Organizing Maps// Archives of Acoustics. -Vol. 40, iss. 4 (2015), s.513-525
DOI:: Digital Object Identifier (open in new tab) 10.1515/aoa-2015-0051
Verified by:: Gdańsk University of Technology