Exploring music with a probabilistic projection interface

Vad, B., Williamson, J., Boland, D., Murray-Smith, R. and Steffensen, P. (2015) Exploring music with a probabilistic projection interface. In: Machine Learning for Music Discovery Workshop, Lille, France, 11 Jul 2015,

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Abstract

We present the design and evaluation of an in- teractive tool for music exploration, with musi- cal mood and genre inferred directly from tracks. It uses probabilistic representations of multivari- able predictions of subjective characteristics of the music to give users subtle, nuanced visuali- sations of the 2D map. These explicitly repre- sent the uncertainty and overlap among features and support music exploration and casual playlist generation. A longitudinal trial in users’ homes showed that probabilistic highlighting of subjec- tive features led to more focused exploration in mouse activity logs, and 6 of 8 users preferred the probabilistic highlighting.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Boland, Mr Daniel and Williamson, Dr John
Authors: Vad, B., Williamson, J., Boland, D., Murray-Smith, R., and Steffensen, P.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2015 The Authors
Publisher Policy:Reproduced under a Creative Commons License
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