Mostra el registre parcial de l'element

dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorIriondo Sanz, Ignasi
dc.contributor.authorPlanet García, Santiago
dc.date.accessioned2020-04-28T14:02:36Z
dc.date.accessioned2023-10-02T06:40:14Z
dc.date.available2020-04-28T14:02:36Z
dc.date.available2023-10-02T06:40:14Z
dc.date.created2012
dc.date.issued2012-09
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3399
dc.description.abstractThe automatic analysis of speech to detect affective states may improve the way users interact with electronic devices. However, the analysis only at the acoustic level could be not enough to determine the emotion of a user in a realistic scenario. In this paper we analyzed the spontaneous speech recordings of the FAU Aibo Corpus at the acoustic and linguistic levels to extract two sets of features. The acoustic set was reduced by a greedy procedure selecting the most relevant features to optimize the learning stage. We compared two versions of this greedy selection algorithm by performing the search of the relevant features forwards and backwards. We experimented with three classification approaches: Nave-Bayes, a support vector machine and a logistic model tree, and two fusion schemes: decision-level fusion, merging the hard-decisions of the acoustic and linguistic classifiers by means of a decision tree; and feature-level fusion, concatenating both sets of features before the learning stage. Despite the low performance achieved by the linguistic data, a dramatic improvement was achieved after its combination with the acoustic information, improving the results achieved by this second modality on its own. The results achieved by the classifiers using the parameters merged at feature level outperformed the classification results of the decision-level fusion scheme, despite the simplicity of the scheme. Moreover, the extremely reduced set of acoustic features obtained by the greedy forward search selection algorithm improved the results provided by the full set.eng
dc.format.extent8 p.
dc.language.isoeng
dc.publisherUniversidad Internacional de La Rioja (UNIR)
dc.relation.ispartofInternational Journal of Interactive Multimedia and Artificial Intelligence, 2012, Vol. 1, No. 6 (Setembre)
dc.rightsAttribution 4.0 International
dc.rights© L'autor/a
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherReconeixement automàtic de la parla
dc.subject.otherProcessament de la parla
dc.subject.otherLingüística computacional
dc.titleComparative Study on Feature Selection and Fusion Schemes for Emotion Recognition from Speech
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscap
dc.subject.udc62
dc.identifier.doihttps://doi.org/10.9781/ijimai.2012.166


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Mostra el registre parcial de l'element

Attribution 4.0 International
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