Joyful for you and tender for us: the influence of individual characteristics and language on emotion labeling and classification

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  • dc.contributor.author Gómez Cañón, Juan Sebastián
  • dc.contributor.author Cano, Estefanía
  • dc.contributor.author Herrera Boyer, Perfecto, 1964-
  • dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
  • dc.date.accessioned 2020-10-28T09:07:10Z
  • dc.date.available 2020-10-28T09:07:10Z
  • dc.date.issued 2020
  • dc.description Comunicació presentada a: International Society for Music Information Retrieval Conference celebrat de l'11 al 16 d'octubre de 2020 de manera virtual.
  • dc.description.abstract Tagging a musical excerpt with an emotion label may result in a vague and ambivalent exercise. This subjectivity entangles several high-level music description tasks when the computational models built to address them produce predictions on the basis of a "ground truth". In this study, we investigate the relationship between emotions perceived in pop and rock music (mainly in Euro-American styles) and personal characteristics from the listener, using language as a key feature. Our goal is to understand the influence of lyrics comprehension on music emotion perception and use this knowledge to improve Music Emotion Recognition (MER) models. We systematically analyze over 30K annotations of 22 musical fragments to assess the impact of individual differences on agreement, as defined by Krippendorff's α coefficient. We employ personal characteristics to form group-based annotations by assembling ratings with respect to listeners' familiarity, preference, lyrics comprehension, and music sophistication. Finally, we study our group-based annotations in a two-fold approach: (1) assessing the similarity within annotations using manifold learning algorithms and unsupervised clustering, and (2) analyzing their performance by training classification models with diverse "ground truths". Our results suggest that a) applying a broader categorization of taxonomies and b) using multi-label, group-based annotations based on language, can be beneficial for MER models.en
  • dc.description.sponsorship The research work conducted in the Music TechnologyGroup at the Universitat Pompeu Fabra is partially sup-ported by the European Commission under the TROMPAproject (H2020 77037).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Gómez-Cañón JS, Cano E, Herrera P, Gómez E. Joyful for you and tender for us: the influence of individual characteristics and language on emotion labeling and classification. In: Cumming J, Ha Lee J, McFee B, Schedl M, Devaney J, McKay C, Zagerle E, de Reuse T, editors. Proceedings of the 21st International Society for Music Information Retrieval Conference; 2020 Oct 11-16; Montréal, Canada. [Canada]: ISMIR; 2020. p. 853-60.
  • dc.identifier.uri http://hdl.handle.net/10230/45600
  • dc.language.iso eng
  • dc.publisher International Society for Music Information Retrieval (ISMIR)
  • dc.relation.ispartof Cumming J, Ha Lee J, McFee B, Schedl M, Devaney J, McKay C, Zagerle E, de Reuse T, editors. Proceedings of the 21st International Society for Music Information Retrieval Conference; 2020 Oct 11-16; Montréal, Canada. [Canada]: ISMIR; 2020.
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/77037
  • dc.rights © Juan Sebastián Gómez-Cañón, Estefanía Cano, Perfecto Herrera, Emilia Gómez. Licensed under a Creative Commons Attribution4.0 International License (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/legalcode) Attribution: Juan Sebastián Gómez-Cañón, Estefanía Cano, Perfecto Herrera, Emilia Gómez, “Joyful for you and tender for us: the influence of individual characteristics and language on emotion labeling and classification”, in Proc. of the 21st Int. Society for Music Information Retrieval Conf., Montréal, Canada, 2020.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri https://creativecommons.org/licenses/by/4.0/
  • dc.title Joyful for you and tender for us: the influence of individual characteristics and language on emotion labeling and classification
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/publishedVersion

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