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Pitch contour segmentation for computer-aided jinju singing training

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dc.contributor.author Gong, Rong
dc.contributor.author Yang, Yile
dc.contributor.author Serra, Xavier
dc.date.accessioned 2017-07-19T09:06:08Z
dc.date.available 2017-07-19T09:06:08Z
dc.date.issued 2016
dc.identifier.citation Gong R, Yang Y, Serra X. Pitch contour segmentation for computer-aided jinju singing training. In: Großmann R, Hajdu G, editors. SMC 2016. 13th Sound & Music Computing Conference; 2016 Aug 31-Sep 3; Hamburg, Germany. Hamburg: Hochschule für Musik und Theater Hamburg; 2016. p. 172-8.
dc.identifier.uri http://hdl.handle.net/10230/32577
dc.description Comunicació presentada a: 13th Sound and Music Computing Conference (SMC 2016), celebrat a Hamburg (Alemanya), del 31 d'agost a 3 de setembre de 2016.
dc.description.abstract Imitation is the main approach of jingju (also known as Beijing opera) singing training through its inheritance of nearly 200 years. Students learn singing by receiving auditory and gestural feedback cues. The aim of computeraided training is to visually reveal the student’s intonation problem by representing the pitch contour on segmentlevel. In this paper, we propose a technique for this purpose. Pitch contour of each musical note is segmented automatically by a melodic transcription algorithm incorporated with a genre-specific musicological model of jingju singing: bigram note transition probabilities defining the probabilities of a transition from one note to another. A finer segmentation which takes into account the high variability of steady segments in jingju context enables us to analyze the subtle details of the intonation by subdividing the note’s pitch contour into a chain of three basic vocal expression segments: steady, transitory and vibrato. The evaluation suggests that this technique outperforms the state of the art methods for jingju singing. The web prototype implementation of these techniques offers a great potential for both in-class learning and self-learning.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Zentrum für Mikrotonale Musik und Multimediale Komposition (ZM4) Hochschule für Musik und Theate
dc.relation.ispartof Großmann R, Hajdu G, editors. SMC 2016. 13th Sound & Music Computing Conference; 2016 Aug 31-Sep 3; Hamburg, Germany. Hamburg: Hochschule für Musik und Theater Hamburg; 2016. p. 172-8.
dc.rights © 2016 Rong Gong, Yile Yang, Xavier Serra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.title Pitch contour segmentation for computer-aided jinju singing training
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Beijing opera
dc.subject.keyword Jingju
dc.subject.keyword Pitch contour
dc.subject.keyword Segmentation
dc.subject.keyword Singing training
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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