Repertoire-specific vocal pitch data generation for improved melodic analysis of carnatic music

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• dc.contributor.author Plaja-Roglans, Genís
• dc.contributor.author Nutall, Thomas
• dc.contributor.author Pearson, Lara
• dc.contributor.author Serra, Xavier
• dc.contributor.author Miron, Marius
• dc.date.accessioned 2024-11-18T12:03:50Z
• dc.date.available 2024-11-18T12:03:50Z
• dc.date.issued 2023
• dc.description.abstract Deep Learning methods achieve state-of-the-art in many tasks, including vocal pitch extraction. However, these methods rely on the availability of pitch track annotations without errors, which are scarce and expensive to obtain for Carnatic Music. Here we identify the tradition-related challenges and propose tailored solutions to generate a novel, large, and open dataset, the Saraga-Carnatic-Melody-Synth (SCMS), comprising audio mixtures and time-aligned vocal pitch annotations. Through a cross-cultural evaluation leveraging this novel dataset, we show improvements in the performance of Deep Learning vocal pitch extraction methods on Indian Art Music recordings. Additional experiments show that the trained models outperform the currently used heuristic-based pitch extraction solutions for the computational melodic analysis of Carnatic Music and that this improvement leads to better results in the musicologically relevant task of repeated melodic pattern discovery when evaluated using expert annotations. The code and annotations are made available for reproducibility. The novel dataset and trained models are also integrated into the Python package compIAM1 which allows them to be used out-of-the-box.
• dc.description.sponsorship This work is funded by the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU) and the Agencia Estatal de Investigación (AEI) within the Musical AI Project – PID2019-111403GB-I00/AEI/10.13039/501100011033.
• dc.format.mimetype application/pdf
• dc.identifier.citation Plaja-Roglans G, Nutall T, Pearson L, Serra X, Miron M. Repertoire-specific vocal pitch data generation for improved melodic analysis of carnatic music. Transactions of the International Society for Music Information Retrieval. 2023;6(1):13-26. DOI: 10.5334/tismir.137
• dc.identifier.doi http://dx.doi.org/10.5334/tismir.137
• dc.identifier.issn 2514-3298
• dc.identifier.uri http://hdl.handle.net/10230/68725
• dc.language.iso eng
• dc.publisher International Society for Music Information Retrieval (ISMIR)
• dc.relation.ispartof Transactions of the International Society for Music Information Retrieval. 2023;6(1):13-26
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-111403GB-I00
• dc.rights © 2023 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Carnatic music
• dc.subject.keyword Data generation
• dc.subject.keyword Vocal pitch extraction
• dc.subject.keyword Melodic pattern discovery
• dc.title Repertoire-specific vocal pitch data generation for improved melodic analysis of carnatic music
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion