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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorTrilla Castelló, Alexandre
dc.contributor.authorAlías Pujol, Francesc
dc.date.accessioned2020-07-06T12:02:39Z
dc.date.accessioned2023-07-13T09:51:51Z
dc.date.available2020-07-06T12:02:39Z
dc.date.available2023-07-13T09:51:51Z
dc.date.issued2009-09-06
dc.identifier.urihttp://hdl.handle.net/20.500.14342/2876
dc.description.abstractThis paper presents a text classifier for automatically taggingthe sentiment of input text according to the emotion that is beingconveyed. This system has a pipelined framework composedof Natural Language Processing modules for feature extractionand a hard binary classifier for decision making between posi-tive and negative categories. To do so, the Semeval 2007 datasetcomposed of sentences emotionally annotated is used for train-ing purposes after being mapped into a model of affect. Theresulting scheme stands a first step towards a complete emotionclassifier for a future automatic expressive text-to-speech syn-thesizer.eng
dc.format.extent4 p.cat
dc.language.isoengcat
dc.publisher10th Annual Conference of the International Speech Communication Association. INTERSPEECH 2009cat
dc.rights© International Speech Communitacion Association. Tots els drets reservats
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherParlacat
dc.subject.otherProcessament de la parlacat
dc.titleSentiment classification in English from sentence-levelannotations of emotions regarding models of affectcat
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersioncat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat


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