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

Alexandre Trilla, Francesc Alías

Producción científica: Artículo en revista indizadaArtículo de conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

This paper presents a text classifier for automatically tagging the sentiment of input text according to the emotion that is being conveyed. This system has a pipelined framework composed of Natural Language Processing modules for feature extraction and a hard binary classifier for decision making between positive and negative categories. To do so, the Semeval 2007 dataset composed of sentences emotionally annotated is used for training purposes after being mapped into a model of affect. The resulting scheme stands a first step towards a complete emotion classifier for a future automatic expressive text-to-speech synthesizer.

Idioma originalInglés
Páginas (desde-hasta)516-519
Número de páginas4
PublicaciónProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
EstadoPublicada - 2009
Evento10th Annual Conference of the International Speech Communication Association, INTERSPEECH 2009 - Brighton, Reino Unido
Duración: 6 sept 200910 sept 2009

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