Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect

This 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 betwe...

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Detalhes bibliográficos
Autores: Trilla Castelló, Alexandre, Alías-Pujol, Francesc
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:España
Recursos:Universitat Ramon Llull (URL)
Repositorio:DAU Arxiu Digital de la Universitat Ramon Llull
OAI Identifier:oai:dau.url.edu:20.500.14342/2876
Acesso em linha:http://hdl.handle.net/20.500.14342/2876
Access Level:acceso abierto
Palavra-chave:Parla
Processament de la parla
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spelling Sentiment classification in English from sentence-levelannotations of emotions regarding models of affectTrilla Castelló, AlexandreAlías-Pujol, FrancescParlaProcessament de la parlaThis 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.10th Annual Conference of the International Speech Communication Association. INTERSPEECH 2009Universitat Ramon Llull. La Salle20202023202020232009info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion4 p.application/pdfhttp://hdl.handle.net/20.500.14342/2876RECERCAT (Dipòsit de la Recerca de Catalunya)reponame:DAU Arxiu Digital de la Universitat Ramon Llullinstname:Universitat Ramon Llull (URL)Inglés© International Speech Communitacion Association. Tots els drets reservatsinfo:eu-repo/semantics/openAccessoai:dau.url.edu:20.500.14342/28762026-06-21T06:40:37Z
dc.title.none.fl_str_mv Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
title Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
spellingShingle Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
Trilla Castelló, Alexandre
Parla
Processament de la parla
title_short Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
title_full Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
title_fullStr Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
title_full_unstemmed Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
title_sort Sentiment classification in English from sentence-levelannotations of emotions regarding models of affect
dc.creator.none.fl_str_mv Trilla Castelló, Alexandre
Alías-Pujol, Francesc
author Trilla Castelló, Alexandre
author_facet Trilla Castelló, Alexandre
Alías-Pujol, Francesc
author_role author
author2 Alías-Pujol, Francesc
author2_role author
dc.contributor.none.fl_str_mv Universitat Ramon Llull. La Salle
dc.subject.none.fl_str_mv Parla
Processament de la parla
topic Parla
Processament de la parla
description This 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.
publishDate 2009
dc.date.none.fl_str_mv 2009
2020
2020
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.14342/2876
url http://hdl.handle.net/20.500.14342/2876
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv © International Speech Communitacion Association. Tots els drets reservats
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © International Speech Communitacion Association. Tots els drets reservats
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 4 p.
application/pdf
dc.publisher.none.fl_str_mv 10th Annual Conference of the International Speech Communication Association. INTERSPEECH 2009
publisher.none.fl_str_mv 10th Annual Conference of the International Speech Communication Association. INTERSPEECH 2009
dc.source.none.fl_str_mv RECERCAT (Dipòsit de la Recerca de Catalunya)
reponame:DAU Arxiu Digital de la Universitat Ramon Llull
instname:Universitat Ramon Llull (URL)
instname_str Universitat Ramon Llull (URL)
reponame_str DAU Arxiu Digital de la Universitat Ramon Llull
collection DAU Arxiu Digital de la Universitat Ramon Llull
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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