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

被引：0
|
作者：
Trilla, Alexandre [1 ]
Alias, Francesc [1 ]
机构：
[1] La Salle Univ Ramon Llull, GTM Grp Recerca Tecnol Media, Barcelona, Spain
来源：
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5 | 2009年
关键词：
natural language processing; text categorization; emotion tagging; sentiment classification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：508 / 511
页数：4
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