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Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook

Ye, Liang and Ferdinando, Hany and Alasaarela, Esko (2014) Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook. Journal of Pattern Recognition Research, 9 (1). pp. 50-63. ISSN 1558-884X

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    Abstract

    School bullying is a serious problem among teenagers. With the development of sensor technology and pattern recognition algorithms, several approaches for detecting school bullying have been developed, namely speech emotion recognition, mental stress recog- nition, and activity recognition. This paper reviews some related work and makes some comparisons among these three aspects. The paper analyzes commonly used features and classifiers, and describes some examples. The Gaussian Mixture Model and the Double Threshold classifiers provided high accuracies in many experiments. By using a combined architecture of classifiers, the results could be further improved. According to the results of the experiments, the six basic emotions, high mental stress and irregular movements can be recognized with high accuracies. So the three types of pattern recognition can be used for school bullying detection effectively. And these techniques can be used on consumer devices such as smartphones to protect teenagers.

    Item Type: Article
    Uncontrolled Keywords: pattern recognition, speech emotion recognition, mental stress recognition, activity recognition, school bullying
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Divisions: Faculty of Industrial Technology > Electrical Engineering Department
    Depositing User: Admin
    Date Deposited: 02 Oct 2014 21:09
    Last Modified: 22 Jul 2019 05:11
    URI: http://repository.petra.ac.id/id/eprint/16993

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