NDLI: Visualization of Music Collections Based on Structural Content Similarity

Content Provider	IEEE Xplore Digital Library
Author	Soriano, A. Paulovich, F. Nonato, L.G. Oliveira, M.C.F.
Copyright Year	2014
Description	Author affiliation: Inst. de Cienc. Mat. e de Comput., Univ. of Sao Paulo, Sao Carlos, Brazil (Soriano, A.; Paulovich, F.; Nonato, L.G.; Oliveira, M.C.F.)
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.
Starting Page	25
Ending Page	32
File Size	833288
Page Count	8
File Format	PDF
ISBN	9781479942589
ISSN	15301834
DOI	10.1109/SIBGRAPI.2014.53
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Feature extraction Data visualization Vectors Compass Color Layout Similarity-based Visualizations Visualization of Music Collections Multidimensional Projection High-Dimensional Data Visualization
Content Type	Text

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