<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-13T04:16:25Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10230/52184" metadataPrefix="marc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10230/52184</identifier><datestamp>2025-12-22T13:41:53Z</datestamp><setSpec>com_2072_6</setSpec><setSpec>col_2072_452952</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Gómez Cañón, Juan Sebastián</subfield>
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      <subfield code="a">Herrera Boyer, Perfecto, 1964-</subfield>
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      <subfield code="a">Cano, Estefanía</subfield>
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      <subfield code="a">Gómez Gutiérrez, Emilia, 1975-</subfield>
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      <subfield code="c">2022-01-11T10:37:03Z</subfield>
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      <subfield code="c">2022-01-11T10:37:03Z</subfield>
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      <subfield code="c">2021</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">This work presents an initial proof of concept of how Music Emotion Recognition (MER) systems could be intentionally biased with respect to annotations&#xd;
&#xd;
of musically-induced emotions in a political context. In specific, we analyze&#xd;
traditional Colombian music containing politically-charged lyrics of two types:&#xd;
(1) vallenatos and social songs from the “left-wing” guerrilla Fuerzas Armadas&#xd;
Revolucionarias de Colombia (FARC) and (2) corridos from the “right-wing”&#xd;
paramilitaries Autodefensas Unidas de Colombia (AUC). We train personalized&#xd;
machine learning models to predict induced emotions for three users with diverse&#xd;
political views – we aim at identifying the songs that may induce negative emotions&#xd;
&#xd;
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&#xd;
&#xd;
could in turn be used to influence the user in a human-centered machine learning&#xd;
environment. In short, highly desired “emotion regulation” applications could&#xd;
potentially deviate to “emotion manipulation” – the recent discredit of emotion&#xd;
recognition technologies might transcend ethical issues of diversity and inclusion.</subfield>
   </datafield>
   <datafield ind2=" " ind1=" " tag="520">
      <subfield code="a">The research work conducted at the Universitat Pompeu Fabra is partially supported by the Eu-&#xd;
ropean Commission under the TROMPA project (H2020 770376) and the Project Musical AI -&#xd;
&#xd;
PID2019-111403GB-I00/AEI/10.13039/501100011033 funded by the Spanish Ministerio de Ciencia,&#xd;
Innovación y Universidades (MCIU) and the Agencia Estatal de Investigación (AEI).</subfield>
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   <datafield ind2="0" ind1="0" tag="245">
      <subfield code="a">Personalized musically induced emotions of not-so-popular Colombian music</subfield>
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