Open Access Open Access  Restricted Access Subscription or Fee Access

Emotion Recognition from Text-a Survey

Pallavi D. Phalke, Dr.M. Emmanuel

Abstract


Emotion is a very important facet of human behaviour which affect on the way people interact in the society. In recent year many methods on human emotions recognition have been published such as recognizing emotion from facial expression and gestures, speech and by written text. This paper focuses on classification of emotion expressed by the online text, based on pre-defined list of emotion. The collection of dataset is the basic step, which is collected from the various sources like daily used sentences, user status from various social networking websites such as facebook and twitter. Using this data set we target only on the keywords that show human emotions. The targeted keywords are extracted from the dataset and translated into the format which can be processed by the classifier to finally generate the Predicting model which is further compared by the test dataset to give the emotions in the input sentences or documents.

Keywords


Affective Computing, Classification, Document Categorization, Emotion Detections.

Full Text:

PDF

References


2. Tim M.H. Li, Michael Chau, Paul W.C. Wong, and Paul S.F. Yip"A Hybrid System for Online Detection of Emotional Distress" PAISI 2012, LNCS 7299 Springer-Verlag Berlin Heidelberg 2012M, 73–80.

Abbasi, A., Chen, H., Thoms, S., Fu, T.: “Affect Analysis of Web Forums and Blogs Using Correlation Ensembles.” IEEE Transactions on Knowledge and Data Engineering (2008) ,1168–1180.

T. Wilson, J. Wiebe, and R. Hwa, “Just how mad are you? Finding strong and weak opinion clauses,” Proc. 21st Conference of the American Association for Artificial Intelligence Jul. 2007, 761-769.

D. B. Bracewell, “Semi-Automatic Creation of an Emotion Dictionary Using WordNet and its Evaluation,” Proc. IEEE conference on Cybernetics and Intelligent Systems, IEEE Press, Sep. 2008, 21-24.

J. Yang, D. B. Bracewell, F. Ren, and S. Kuroiwa, “The Creation of a Chinese Emotion Ontology Based on HowNet”, Engineering Letters, Feb. 2008,166-171.

C.-H. Wu, Z.-J.Chuang, and Y.-C. Lin, “Emotion Recognition from Text Using Semantic Labels and Separable Mixture Models,” ACM Transactions on Asian Language Information Processing Jun. 2006, 165-183.

Z. Teng, F. Ren, and S. Kuroiwa, “Recognition of Emotion with SVMs,” in Lecture Notes of Artificial Intelligence Eds.Springer, Berlin Heidelberg, 2006,701-710 .

C. Yang, K. H.-Y. Lin, and H.-H. Chen, “Emotion classification using web blog corpora,” Proc. IEEE/WIC/ACM International Conference on Web Intelligence. IEEE Computer Society, Nov. 2007, 275-278.

C. M. Lee, S. S. Narayanan, and R. Pieraccini, "Combining Acoustic and Language Information for Emotion Recognition," Proc. 7th International Conference on Spoken Language Processing (ICSLP 02), 2002, 873-876. [10]http://www.affectivesciences.org/reserachmaterial

http://www.weka.net.nz/


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.