Personalized musically induced emotions of not-so-popular Colombian music

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  • dc.contributor.author Gómez Cañón, Juan Sebastián
  • dc.contributor.author Herrera Boyer, Perfecto, 1964-
  • dc.contributor.author Cano, Estefanía
  • dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
  • dc.date.accessioned 2022-01-11T10:37:03Z
  • dc.date.available 2022-01-11T10:37:03Z
  • dc.date.issued 2021
  • dc.description Comunicació presentada al workshop Human Centered AI inclòs a: 35th Conference on Neural Information Processing Systems (NeurIPS 2021) celebrat el 13 de desembre de manera virtual.
  • dc.description.abstract This work presents an initial proof of concept of how Music Emotion Recognition (MER) systems could be intentionally biased with respect to annotations of musically-induced emotions in a political context. In specific, we analyze traditional Colombian music containing politically-charged lyrics of two types: (1) vallenatos and social songs from the “left-wing” guerrilla Fuerzas Armadas Revolucionarias de Colombia (FARC) and (2) corridos from the “right-wing” paramilitaries Autodefensas Unidas de Colombia (AUC). We train personalized machine learning models to predict induced emotions for three users with diverse political views – we aim at identifying the songs that may induce negative emotions for a particular user, such as anger and fear. To this extent, a user’s emotion judgements could be interpreted as problematizing data – subjective emotional judgments could in turn be used to influence the user in a human-centered machine learning environment. In short, highly desired “emotion regulation” applications could potentially deviate to “emotion manipulation” – the recent discredit of emotion recognition technologies might transcend ethical issues of diversity and inclusion.
  • dc.description.sponsorship The research work conducted at the Universitat Pompeu Fabra is partially supported by the Eu- ropean Commission under the TROMPA project (H2020 770376) and the Project Musical AI - PID2019-111403GB-I00/AEI/10.13039/501100011033 funded by the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU) and the Agencia Estatal de Investigación (AEI).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Gómez-Cañón JS, Herrera P, Cano E, Gómez E. Personalized musically induced emotions of not-so-popular Colombian music. Paper presented at: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Human Centered AI workshop ; 2021 Dec 13; Sydney, Australia.
  • dc.identifier.uri http://hdl.handle.net/10230/52184
  • dc.language.iso eng
  • dc.publisher NeurIPS
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/770376
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-111403GB-I00
  • dc.rights © The Authors. This paper is licensed under a Creative Commons License (Attribution-NonCommercial 4.0 International (CC BY-NC 4.0))
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
  • dc.title Personalized musically induced emotions of not-so-popular Colombian music
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/publishedVersion

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