A Survey of Style Identification Approaches in Music Information Retrieval

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-36 Number-1
Year of Publication : 2016
Authors : Santosh Pakhare, Mrs M. A. Potey
  10.14445/22312803/IJCTT-V36P104

MLA

Santosh Pakhare, Mrs M. A. Potey "A Survey of Style Identification Approaches in Music Information Retrieval". International Journal of Computer Trends and Technology (IJCTT) V36(1):17-21, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
One of the problems to solve in Music Information Retrieval (MIR) is the modelization of music style. The system could be trained to identify the main features that would characterize music genres or style so as to look for that kind of music over large musical corpus. So in this paper multimodal approach, pattern recognition approach and co-updating approach is been studied for identifying the style from different genre of the music. Considering the intuitive feelings of similarity from the listeners perspective, the focus on features that are computed using similarity metrics for melodies, harmonies, and audio signals for style identification. A multimodal approach mostly considered support vector machine as a binary classifier to determine if two songs or music played by the same artist given their similarity metrics in the three aspects and also discussed the experimental methodologies of the two different approaches.

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Keywords
Gaussian mixture models, melodic contour, music similarity, n-grams, style.