Title
Visualization of music collections based on structural content similarity
Date Issued
01 October 2014
Access level
metadata only access
Resource Type
conference paper
Author(s)
Paulovich F.
Nonato L.G.
Oliveira M.C.F.
Universidad de São Paulo
Publisher(s)
IEEE Computer Society
Abstract
Users interact a lot with their personal music collections, typically using standard text-based interfaces that offer constrained functionalities based on assigned metadata or tags. Alternative visual interfaces have been developed, both to display graphical views of music collections that attempt to reflect some chosen property or organization, or to display abstract visual representations of specific songs. Yet, there are many dimensions involved in the perception and handling of music and mapping musical information into computer tractable models is a challenging problem. With a wide variety of possible approaches, the search for novel strategies to visually represent songs and/or collections persists, targeted either at the general public or at musically trained individuals. In this paper we describe a visual interface to browse music collections that relies on a graphical metaphor designed to convey the underlying musical structure of a song. An iconic representation of individual songs is coupled with a spatial placement of songs that reflects their structural similarity. The song icon is derived from features extracted from MIDI files, rather than from audio signals. The very nature of MIDI descriptions enables the identification of simple, yet meaningful, musical structures, allowing us to extract features that support both creating the icon and comparing songs. A similarity-based spatial placement is created projecting the feature vectors with the Least Square Projection multidimensional projection, employing the Dynamic Time Warping distance function to evaluate feature similarity. We describe the process of generating such visual representations and illustrate potentially interesting usage scenarios.
Start page
25
End page
32
Language
English
OCDE Knowledge area
Ciencias de la computación Música
Scopus EID
2-s2.0-84908000719
Source
Brazilian Symposium of Computer Graphic and Image Processing
ISSN of the container
15301834
Sources of information: Directorio de Producción Científica Scopus