10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Sentiment Classification in English from Sentence-Level Annotations of Emotions Regarding Models of Affect

Alexandre Trilla, Francesc Alías

Universitat Ramon Llull, Spain

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.

Full Paper

Bibliographic reference.  Trilla, Alexandre / Alías, Francesc (2009): "Sentiment classification in English from sentence-level annotations of emotions regarding models of affect", In INTERSPEECH-2009, 516-519.