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A Novel Approach for Detecting Emotion in Text
Objectives: In this paper, we present an experiment, which concerned with detection of emotion class at sentence level. Methods: Approach is based upon combination of both machine leaning and key word based approach. There is a large annotated data set which manually classified a sentence beyond six basic emotions: love, joy, anger, sadness, fear, surprise. Findings: Using annotated data set define an emotion vector of key word in input sentence. Novelty: Using an algorithm calculate the emotion vector of sentence by emotion vector of word. Then on the basis of emotion vector categorized the sentence into appropriate emotion class. Results are shown and found good in comparison to individual approach.
Emotion Detection, Emotion Vecotor, Machine Learning, Natural Language Processing, Sentence Level.
- Ortony A, Clore GL, Collins A. The cognitive structure of emotions. Cambridge university press; 1990 May 25.
- Garett B. Brain and behaviour: an introduction to biopsychology, 2nd ed. SAGE Publications, 2009.
- Ma C, Prendinger H, Ishizuka M. Emotion estimation and reasoning based on affective textual interaction. In Affective Computing and Intelligent Interaction, Springer Berlin Heidelberg. 2005 Oct 22; 622–8.
- Cohn JF, Katz GS. Bimodal expression of emotion by face and voice. Proceedings of the sixth ACM international conference on Multimedia: Face/gesture recognition and their applications, ACM. 1998 Sep 1; 41–4.
- De Silva LC, Ng PC. Bimodal emotion recognition. Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition, IEEE. 2000. p. 332–5.
- Devillers L, Lamel L, Vasilescu I. Emotion detection in task-oriented spoken dialogues. 2003 Proceedings International Conference on Multimedia and Expo, ICME’03, IEEE. 2003 Jul 63; 549 pp.
- Nguyen T, Bass I, Li M, Sethi IK. Investigation of combining SVM and decision tree for emotion classification. Seventh IEEE International Symposium on Multimedia, IEEE. 2005 Dec 12; 5 pp.
- Yanaru T. An emotion processing system based on fuzzy inference and subjective observations. 1995 Proceedings Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, IEEE. 1995 Nov 20; 15–20.
- Lee Y-H, Ahn H, Cho H-J, Lee J-H. Recognition of facial emotion through face analysis based on quadratic bezier curves. Indian Journal of Science and Technology. 2015 Dec; 8(35). Doi:10.17485/ijst/2015/v8i35/86092.
- Subhashree R, Rathna GN. Speech Emotion Recognition: Performance Analysis based on Fused Algorithms and GMM Modelling. Indian Journal of Science and Technology. 2016; 9(11). Doi: 10.17485/ijst/2016/v9i11/88460.
- Alm EC. Affect in text and speech. Pro Quest; 2008.
- Teng Z, Ren F, Kuroiwa S. Retracted: recognition of emotion with SVMs. In Computational Intelligence, Springer Berlin Heidelberg. 2006 Aug 16; 701–10.
- Yang C, Lin KH, Chen HH. Emotion classification using web blog corpora. IEEE/WIC/ACM International Conference on Web Intelligence, IEEE. 2007 Nov 2. p. 275–8.
- Wu CH, Chuang ZJ, Lin YC. Emotion recognition from text using semantic labels and separable mixture models. ACM transactions on Asian language information processing (TALIP). 2006 Jun 1; 5(2):165–83.
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