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Paper Abstract and Keywords
Presentation 2020-02-14 16:10
Performance evaluation of bullying voice judgement system using emotion analysis based on SVM
Takahiro Ueno, Shintaro Mori, Masayoshi Ohashi (Fukuoka Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Bullying is a serious problem all over the world, and bullying detection is significant to protect victims. In this paper, we propose the bullying detection system using speech emotion recognition. The proposed system detects bullying for emotional voice. Emotional voice consists of emotional bullying voice and emotional non-bullying voice. The proposed system detects emotional bullying voice by Support Vector Machine (SVM). Emotional voice is processed frame shift. Emotional voice is extracted feature by acoustic analysis and emotion analysis of SVM. In the experiment, we evaluate the accuracy of the proposed system after splitting emotional bullying voice into training data and test data. Training data of emotional bullying voice is natural voice that is collected subjectively. Test data of emotional bullying voice is acting voice that is collected subjectively.
Keyword (in Japanese) (See Japanese page) 
(in English) Bullying / Emotion Rcognition / Support Vector Machine(SVM) / / / / /  
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Conference Information
Committee HPB  
Conference Date 2020-02-14 - 2020-02-14 
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Paper Information
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Conference Code 2020-02-HPB 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance evaluation of bullying voice judgement system using emotion analysis based on SVM 
Sub Title (in English)  
Keyword(1) Bullying  
Keyword(2) Emotion Rcognition  
Keyword(3) Support Vector Machine(SVM)  
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1st Author's Name Takahiro Ueno  
1st Author's Affiliation Fukuoka University (Fukuoka Univ.)
2nd Author's Name Shintaro Mori  
2nd Author's Affiliation Fukuoka University (Fukuoka Univ.)
3rd Author's Name Masayoshi Ohashi  
3rd Author's Affiliation Fukuoka University (Fukuoka Univ.)
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Speaker Author-1 
Date Time 2020-02-14 16:10:00 
Presentation Time 15 minutes 
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