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Paper Abstract and Keywords
Presentation 2019-03-12 14:00
Analysis of Radio Speech Using Deep Neural Network
Wataru Yokota, Keiko Ochi, Yasunari Obuchi (Tokyo Univ. Tech)
Abstract (in Japanese) (See Japanese page) 
(in English) Radio broadcasting, which uses audio information only, is still popular in the modern society in which television and movie websites are widely enjoyed. In radio programs, we generally broadcast speech sounds spoken by so called personalities. In this research, we estimated the nonlinguistic information from using machine learning, aiming at creating a audio-based broadcast program retrieving system. More concretely, it was estimated by machine learning whether the speech is a monologue that a speaker is talking alone or dialogue talked by two or more people, using a the acoustic features obtained from the speech waveforms and deep neural network.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Voice / Radio / Feature selection / / / /  
Reference Info. ITE Tech. Rep., vol. 43, no. 9, AIT2019-142, pp. 325-328, March 2019.
Paper #  
Date of Issue 2019-03-05 (AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
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 Radio Speech Using Deep Neural Network 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Voice  
Keyword(3) Radio  
Keyword(4) Feature selection  
1st Author's Name Wataru Yokota  
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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Date Time 2019-03-12 14:00:00 
Presentation Time 135 
Registration for AS 
Paper # ITE-AIT2019-142 
Volume (vol) ITE-43 
Number (no) no.9 
Page pp.325-328 
#Pages ITE-4 
Date of Issue ITE-AIT-2019-03-05 

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