An overview of automatic piano performance assessment within the music education context

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• dc.contributor.author Kim, Hyon
• dc.contributor.author Ramoneda, Pedro
• dc.contributor.author Miron, Marius
• dc.contributor.author Serra, Xavier
• dc.date.accessioned 2022-05-04T12:47:19Z
• dc.date.available 2022-05-04T12:47:19Z
• dc.date.issued 2022
• dc.description Comunicació presentada a la 14th International Conference on Computer Supported Education, celebrada del 22 a 24 d'abril de 2021 de manera virtual.
• dc.description.abstract Piano is one of the most popular instruments among music learners. Technologies to evaluate piano performances have been researched and developed in recent years rapidly, including data driven methods using machine learning. Despite the demand from people and speed of the development, there are still gaps between the methods and the pedagogical setup for real use case scenarios due to lack of accuracy of methods, insufficient amount of training data or the biases in training machine learning models, ignoring actual use case of the technology and such. In this paper, we first propose a feedback approach in piano performance education and review methods for Automated Piano Performance Assessment (APPA). After that, we discuss about gaps between a feedback approach and current methods, emphasizing their music education application. As a future work we propose a potential approach to overcome the gaps.
• dc.description.sponsorship This project is supported by Project Musical AI funded by the Spanish Ministerio de Ciencia, Innovacion y Universidades (MCIU) and the Agencia Estatal de Investigacion (AEI).
• dc.format.mimetype application/pdf
• dc.identifier.citation Kim H, Ramoneda P, Miron M, Serra X. An overview of automatic piano performance assessment within the music education context. In: Cukurova M, Rummel N, Gillet D, McLaren B, Uhomoibhi J, editors. Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: CSME; 2022 Apr 22-24; Prague, Czech Republic. [S.l.]: SCITEPRESS – Science and Technology Publications; 2022. p. 456-74. DOI: 10.5220/0011137600003182
• dc.identifier.doi http://doi.org/10.5220/0011137600003182
• dc.identifier.isbn 9789897585623
• dc.identifier.uri http://hdl.handle.net/10230/52980
• dc.language.iso eng
• dc.publisher SCITEPRESS – Science and Technology Publications
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-111403GB-I00
• dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Contribution presented at CSME 2022, https://csedu.scitevents.org/?y=2022, available at http://doi.org/10.5220/0011137600003182
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0
• dc.subject.keyword Piano Performance Assessment
• dc.subject.keyword Music Education
• dc.subject.keyword Pedagogy
• dc.subject.keyword Music Information Retrieval
• dc.title An overview of automatic piano performance assessment within the music education context
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion