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A Bayesian Approach to Classify the Music Scores on the Basis of the Music Style

  • Michele Della Ventura
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 57)

Abstract

This article presents a new version of the algorithm proposed by Della Ventura (12th TELE-INFO International Conference on Recent Researches in Telecommunications, and Informatics, 2013, [1]) to classify the musical scores. Score classification means an automatic process of assignment of the specific score to a certain class or category: baroque, romantic or contemporary music. The algorithm is based on a Bayesian probabilistic model that extends the Naive Bayes classifier by adding a variable tied to the value of the information contained within the. The score is not seen as a single entity, but as a set of subtopics, every single one of which identifies and represents a standard feature of music writing. The classification of the score is done on the basis of its subtopics: an intermediate level of classification is thus introduced, which induces a hierarchical classification. The new algorithm performs equally well on the old dataset, but gives much better results on the new larger and more diverse dataset.

Keywords

Categorization Document classification Information Music score Naive Bayes 

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Authors and Affiliations

  1. 1.Department of TechnologyMusic Academy “Studio Musica”TrevisoItaly

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