Voice Separation in Polyphonic Music: Information Theory Approach - Artificial Intelligence Applications and Innovations (AIAI 2018) Access content directly
Conference Papers Year : 2018

Voice Separation in Polyphonic Music: Information Theory Approach

Michele Della Ventura
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Abstract

Voice Separation is a delicate stage in a music information retrieval process intended to be used in the automated music analysis processes through textual segmentation or for the indexation of a music score. This article presents a method that is capable of separating polyphonic music, considered in its symbolic aspect, into its individual parts (or voices). This method considers every single note as an individual entity and assigns it to the part (or voice) where the information content that it assumes in relation to the already-existing notes of the same score is maximum. The algorithm may separate the voices identifying them even in the points that intersect. The algorithm was tested against a handful of musical works that were carefully selected from the repertoire of Bach and of Mendelssohn.
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hal-01821044 , version 1 (22-06-2018)

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Michele Della Ventura. Voice Separation in Polyphonic Music: Information Theory Approach. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.638-646, ⟨10.1007/978-3-319-92007-8_54⟩. ⟨hal-01821044⟩
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