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Determining Feature Relevance in Subject Responses to Musical Stimuli

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Mathematics and Computation in Music (MCM 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 38))

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Abstract

This paper presents a method that determines the relevance of a set of signals (musical features) given listener judgments of music in an experimental setting. Rather than using linear correlation methods, we allow for nonlinear relationships and multi-dimensional feature vectors. We first provide a methodology based on polynomial functions and the least-mean-square error measure. We then extend the methodology to arbitrary nonlinear function approximation techniques and introduce the Kullback-Leibler Distance as an alternative relevance metric. The method is demonstrated first with simple artificial data and then applied to analyze complex experimental data collected to examine the perception of musical tension.

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Author information

Authors and Affiliations

  1. Music and Audio Research Laboratory (MARL), New York University, 35 W. 4th St., New York, NY 10012, USA

    Morwaread M. Farbood

  2. ThingMagic Inc., One Broadway, Cambridge, MA 02142, USA

    Bernd Schoner

Authors
  1. Morwaread M. Farbood
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  2. Bernd Schoner
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Editor information

Editors and Affiliations

  1. Viterbi School of Engineering, Integrated Media Systems Center, Epstein Department of Industrial and Systems Engineering, University of Southern California, 3715 McClintock Avenue GER240 MC:0193, P.O. Box, Los Angeles, California, USA

    Elaine Chew

  2. Hugh Hodgson School of Music, University of Georgia, 250 River Road, GA 30602-7278, Athens, USA

    Adrian Childs

  3. Department of Math and Computer Science, Barry University, 11300 NE 2nd Avenue, Miami Shores, FL 33161, USA

    Ching-Hua Chuan

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© 2009 Springer-Verlag Berlin Heidelberg

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Farbood, M.M., Schoner, B. (2009). Determining Feature Relevance in Subject Responses to Musical Stimuli. In: Chew, E., Childs, A., Chuan, CH. (eds) Mathematics and Computation in Music. MCM 2009. Communications in Computer and Information Science, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02394-1_11

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  • DOI: https://doi.org/10.1007/978-3-642-02394-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02393-4

  • Online ISBN: 978-3-642-02394-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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