<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-04628187</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-17T16:26:35+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">MSP-Podcast SER Challenge 2024: L'antenne du Ventoux Multimodal Self-Supervised Learning for Speech Emotion Recognition</title>
            <author role="aut">
              <persName>
                <forename type="first">Jarod</forename>
                <surname>Duret</surname>
              </persName>
              <idno type="halauthorid">2286632-0</idno>
              <affiliation ref="#struct-100376"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Mickael</forename>
                <surname>Rouvier</surname>
              </persName>
              <idno type="halauthorid">807161-0</idno>
              <affiliation ref="#struct-100376"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Yannick</forename>
                <surname>Estève</surname>
              </persName>
              <idno type="halauthorid">2528749-0</idno>
              <affiliation ref="#struct-100376"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>jarod</forename>
                <surname>duret</surname>
              </persName>
              <email type="md5">2871b6b698453b4a53214790f001553c</email>
              <email type="domain">univ-avignon.fr</email>
            </editor>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2024-07-07 16:24:16</date>
              <date type="whenModified">2024-07-09 03:15:32</date>
              <date type="whenReleased">2024-07-08 10:52:29</date>
              <date type="whenProduced">2024-06-18</date>
              <date type="whenEndEmbargoed">2024-06-28</date>
              <ref type="file" target="https://hal.science/hal-04628187v1/document">
                <date notBefore="2024-06-28"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://hal.science/hal-04628187v1/file/Odyssey2024_Challenge-5.pdf" id="file-4628187-4026100">
                <date notBefore="2024-06-28"/>
              </ref>
              <ref type="externalLink" target="http://arxiv.org/pdf/2407.05746"/>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="1436329">
                <persName>
                  <forename>jarod</forename>
                  <surname>duret</surname>
                </persName>
                <email type="md5">2871b6b698453b4a53214790f001553c</email>
                <email type="domain">univ-avignon.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-04628187</idno>
            <idno type="halUri">https://hal.science/hal-04628187</idno>
            <idno type="halBibtex">duret:hal-04628187</idno>
            <idno type="halRefHtml">&lt;i&gt;Odyssey 2024&lt;/i&gt;, Jun 2024, Quebec, France</idno>
            <idno type="halRef">Odyssey 2024, Jun 2024, Quebec, France</idno>
            <availability status="restricted">
              <licence target="https://about.hal.science/hal-authorisation-v1/">HAL Authorization<ref corresp="#file-4628187-4026100"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="UNIV-AVIGNON">Université d'Avignon</idno>
            <idno type="stamp" n="GENCI">Publications ayant eu recours aux supercalculateurs du GENCI</idno>
            <idno type="stamp" n="LIA" corresp="UNIV-AVIGNON">Laboratoire Informatique d'Avignon</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="invited" n="0">No</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
            <note type="proceedings" n="0">No</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">MSP-Podcast SER Challenge 2024: L'antenne du Ventoux Multimodal Self-Supervised Learning for Speech Emotion Recognition</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Jarod</forename>
                    <surname>Duret</surname>
                  </persName>
                  <idno type="halauthorid">2286632-0</idno>
                  <affiliation ref="#struct-100376"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Mickael</forename>
                    <surname>Rouvier</surname>
                  </persName>
                  <idno type="halauthorid">807161-0</idno>
                  <affiliation ref="#struct-100376"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Yannick</forename>
                    <surname>Estève</surname>
                  </persName>
                  <idno type="halauthorid">2528749-0</idno>
                  <affiliation ref="#struct-100376"/>
                </author>
              </analytic>
              <monogr>
                <meeting>
                  <title>Odyssey 2024</title>
                  <date type="start">2024-06-18</date>
                  <settlement>Quebec</settlement>
                  <country key="FR">France</country>
                </meeting>
                <imprint>
                  <date type="datePub">2024-04-15</date>
                </imprint>
              </monogr>
              <idno type="arxiv">2407.05746</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en">Emotion recognition</term>
              </keywords>
              <classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode>
              <classCode scheme="halTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halOldTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halTreeTypology" n="COMM">Conference papers</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>In this work, we detail our submission to the 2024 edition of the MSP-Podcast Speech Emotion Recognition (SER) Challenge. This challenge is divided into two distinct tasks: Categorical Emotion Recognition and Emotional Attribute Prediction. We concentrated our efforts on Task 1, which involves the categorical classification of eight emotional states using data from the MSP-Podcast dataset. Our approach employs an ensemble of models, each trained independently and then fused at the score level using a Support Vector Machine (SVM) classifier. The models were trained using various strategies, including Self-Supervised Learning (SSL) fine-tuning across different modalities: speech alone, text alone, and a combined speech and text approach. This joint training methodology aims to enhance the system's ability to accurately classify emotional states. This joint training methodology aims to enhance the system's ability to accurately classify emotional states. Thus, the system obtained F1-macro of 0.35\% on development set.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="laboratory" xml:id="struct-100376" status="VALID">
          <orgName>Laboratoire Informatique d'Avignon</orgName>
          <orgName type="acronym">LIA</orgName>
          <desc>
            <address>
              <addrLine>339 Chemin des Meinajaries Agroparc BP 1228 84911 Avignon cedex 9</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://lia.univ-avignon.fr/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-195507" type="direct"/>
            <relation active="#struct-302221" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-195507" status="VALID">
          <idno type="ROR">https://ror.org/00mfpxb84</idno>
          <orgName>Avignon Université</orgName>
          <orgName type="acronym">AU</orgName>
          <desc>
            <address>
              <addrLine>74 rue Louis Pasteur - 84 029 Avignon cedex 1</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.univ-avignon.fr/</ref>
          </desc>
        </org>
        <org type="institution" xml:id="struct-302221" status="VALID">
          <orgName>Centre d'Enseignement et de Recherche en Informatique - CERI</orgName>
          <desc>
            <address>
              <country key="FR"/>
            </address>
          </desc>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>