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Paper Abstract and Keywords
Presentation 2019-03-12 14:00
Analysis of Manzai Speech Using Machine Learning
Tetsuya Kamijima, Keiko Ochi, Yasunari Obuchi (Tokyo Univ. Tech.)
Abstract (in Japanese) (See Japanese page) 
(in English) Aiming at autommatic manzai speech evaluation, we analyzed manzai speech using machine learning. In our method, as a preliminary stage of manzai speech evaluation, it is necessary to distinguish between the comedian's speech and the audience's laughter. We applied machine learning to distinguish them. In the experiment, we put labels on the data, segmented the manzai speech, extracted feature, and discriminated them by the speaker manually or using machine learning. We used power spectrum analysis by Python and openSMILE for feature extraction, and Weka for machine learning. As a result of the experiment, we succeeded to discriminate the frames corresponding to the audience. Furthermore, we created a graph representing the frames judged as audience's with the feature quantity, and showed an example of visualization.
Keyword (in Japanese) (See Japanese page) 
(in English) Manzai / Machine Learning / Weka / openSMILE / Python / / /  
Reference Info. ITE Tech. Rep., vol. 43, no. 9, AIT2019-168, pp. 413-416, March 2019.
Paper #  
Date of Issue 2019-03-05 (AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970

Conference Information
Committee AIT IIEEJ AS CG-ARTS  
Conference Date 2019-03-12 - 2019-03-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Waseda Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Expressive Japan 2019 
Paper Information
Registration To AS 
Conference Code 2019-03-AIT-IIEEJ-AS-ARTS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of Manzai Speech Using Machine Learning 
Sub Title (in English)  
Keyword(1) Manzai  
Keyword(2) Machine Learning  
Keyword(3) Weka  
Keyword(4) openSMILE  
Keyword(5) Python  
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1st Author's Name Tetsuya Kamijima  
1st Author's Affiliation Tokyo University of Technology (Tokyo Univ. Tech.)
2nd Author's Name Keiko Ochi  
2nd Author's Affiliation Tokyo University of Technology (Tokyo Univ. Tech.)
3rd Author's Name Yasunari Obuchi  
3rd Author's Affiliation Tokyo University of Technology (Tokyo Univ. Tech.)
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Speaker
Date Time 2019-03-12 14:00:00 
Presentation Time 135 
Registration for AS 
Paper # ITE-AIT2019-168 
Volume (vol) ITE-43 
Number (no) no.9 
Page pp.413-416 
#Pages ITE-4 
Date of Issue ITE-AIT-2019-03-05 


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