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Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system

Micheline Lesaffre (UGent) and Marc Leman (UGent)
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Abstract
This paper explores the potential use of fuzzy logic for semantic music recommendation. We show that a set of affective/emotive, structural and kinaesthetic descriptors can be used to formulate a query which allows the retrieval of intended music. A semantic music recommendation system was built, based on an elaborate study of potential users and an analysis of the semantic descriptors that best characterize the user’s understanding of music. Significant relationships between expressive and structural semantic descriptions of music were found. Fuzzy logic was then applied to handle the quality ratings associated with the semantic descriptions. A working semantic music recommendation system was tested and evaluated. Real-world testing revealed high user satisfaction.

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Chicago
Lesaffre, Micheline, and Marc Leman. 2006. “Using Fuzzy Logic to Handle the Semantic Descriptions of Music in a Content-based Retrieval System.” In Learning the Semantics of Audio Signals (LSAS), ed. Pedro Cano, Andreas Nurnberger, Sebastian Stober, and George Tzanetakis, 43–52. Germany: Otto-von-Guericke-University Magdeburg.
APA
Lesaffre, Micheline, & Leman, M. (2006). Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system. In P. Cano, A. Nurnberger, S. Stober, & G. Tzanetakis (Eds.), Learning the Semantics of Audio Signals (LSAS) (pp. 43–52). Presented at the First International Workshop on Learning the Semantics of Audio Signals, Germany: Otto-von-Guericke-University Magdeburg.
Vancouver
1.
Lesaffre M, Leman M. Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system. In: Cano P, Nurnberger A, Stober S, Tzanetakis G, editors. Learning the Semantics of Audio Signals (LSAS). Germany: Otto-von-Guericke-University Magdeburg; 2006. p. 43–52.
MLA
Lesaffre, Micheline, and Marc Leman. “Using Fuzzy Logic to Handle the Semantic Descriptions of Music in a Content-based Retrieval System.” Learning the Semantics of Audio Signals (LSAS). Ed. Pedro Cano et al. Germany: Otto-von-Guericke-University Magdeburg, 2006. 43–52. Print.
@inproceedings{1085507,
  abstract     = {This paper explores the potential use of fuzzy logic for semantic music recommendation. We show that a set of affective/emotive, structural and kinaesthetic descriptors can be used to formulate a query which allows the retrieval of intended music. A semantic music recommendation system was built, based on an elaborate study of potential users and an analysis of the semantic descriptors that best characterize the user{\textquoteright}s understanding of music. Significant relationships between expressive and structural semantic descriptions of music were found. Fuzzy logic was then applied to handle the 
quality ratings associated with the semantic descriptions. A working semantic music recommendation system was tested and evaluated. Real-world testing revealed high user satisfaction.},
  author       = {Lesaffre, Micheline and Leman, Marc},
  booktitle    = {Learning the Semantics of Audio Signals (LSAS)},
  editor       = {Cano, Pedro  and Nurnberger, Andreas and Stober, Sebastian and Tzanetakis, George},
  isbn         = {3980487423},
  language     = {eng},
  location     = {Athens, Greece},
  pages        = {43--52},
  publisher    = {Otto-von-Guericke-University Magdeburg},
  title        = {Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system},
  year         = {2006},
}