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Emotion classification of text is very important in applications like emotional text-to-speech (TTS) synthesis, human computer interaction, etc. Past studies on emotion classification focus on the writer's emotional state conveyed through the text. This research addresses the reader's emotions provoked by the text. The classification of documents into reader emotion categories has novel applications...
There is a widely held belief in the NLP and computational linguistics communities that identifying and defining roles of predicate arguments in a sentence has a lot of potential for and is a significant step toward improving important applications such as document retrieval, machine translation, question answering and information extraction. In this paper, we present an semantic role labeling (SRL)...
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