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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Publisher's URL: https://sites.google.com/site/ml4md2015/
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 |
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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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