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Vad, B.; Williamson, J.; Boland, D.; Murray-Smith, R.; Steffensen, P. (2015)
Languages: English
Types: Other
Subjects:
We present the design and evaluation of an in-\ud teractive tool for music exploration, with musi-\ud cal mood and genre inferred directly from tracks.\ud \ud It uses probabilistic representations of multivari-\ud able predictions of subjective characteristics of\ud \ud the music to give users subtle, nuanced visuali-\ud sations of the 2D map. These explicitly repre-\ud sent the uncertainty and overlap among features\ud \ud and support music exploration and casual playlist\ud \ud generation. A longitudinal trial in users’ homes\ud \ud showed that probabilistic highlighting of subjec-\ud tive features led to more focused exploration in\ud \ud mouse activity logs, and 6 of 8 users preferred\ud \ud the probabilistic highlighting.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Boland, Daniel, McLachlan, Ross, and Murray-Smith, Roderick. Inferring Music Selections for Casual Music Interaction. EuroHCIR, pp. 15-18, 2013.
    • Boland, Daniel, McLachlan, Ross, and Murray-Smith, Roderick. Engaging with mobile music retrieval. In MobileHCI 2015, Copenhagen, 2015.
    • Pohl, Henning and Murray-Smith, Roderick. Focused and casual interactions: allowing users to vary their level of engagement. In Proc. ACM SIGCHI Conf. on Human Factors in Computing Systems, CHI '13, pp. 2223-2232, New York, NY, USA, 2013. ACM.
    • Rasmussen, Carl Edward and Williams, Christopher K. I. Gaussian Processes for Machine Learning. MIT Press, 2006.
    • Schedl, Markus and Flexer, Arthur. Putting the User in the Center of Music Information Retrieval. In Proc. of the Int. Conf. on Music Information Retrieval (ISMIR), Porto, Portugal, 2012.
    • Stober, Sebastian. Adaptive Methods for User-Centered Organization of Music Collections. PhD thesis, Ottovon-Guericke-Universitt Magdeburg, 2011.
    • Sturm, Bob L. A simple method to determine if a music information retrieval system is a horse. IEEE Transactions on Multimedia, 16(6):1636-1644, 2014.
    • van der Maaten, Laurens and Hinton, Geoffrey. Visualizing Data using t-SNE. Journal of Machine Learning Research, 9:2579-2605, 2008.
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