Context based emotion detection from text input
نویسنده
چکیده
Emotion detection was normally conducted from the viewpoint of prosody and articulation features. There is still an opening question on how to extract the emotion from the text input. To solve the problem, the paper generates an emotion estimation net (ESiN), which combines the content words and emotion functional words to estimate the final emotion output. In the paper, emotion functional words are also classified into emotional keyword, modifier word and metaphor word. To make more detailed word classification, some context information was analyzed. Both experiments and cross tests show that the method could generate the good results for emotion detection from text input.
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تاریخ انتشار 2004