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A Study on the Gender and Age Classification of Speech Data Using CNN
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CNN을 이용한 음성 데이터 성별 및 연령 분류 기술 연구

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Type
Academic journal
Author
Dae-Seo Park (강원대학교) Joon-Il Bang (강원대학교) Hwa-Jong Kim (강원대학교) Young-Jun Ko (모다정보통신)
Journal
Korean Institute of Information Technology The Journal of Korean Institute of Information Technology Vol.16 No.11 KCI Accredited Journals
Published
2018.11
Pages
11 - 21 (11page)
DOI
10.14801/jkiit.2018.16.11.11

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A Study on the Gender and Age Classification of Speech Data Using CNN
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Research is carried out to categorize voices using Deep Learning technology. The study examines neural networkbased sound classification studies and suggests improved neural networks for voice classification. Related studies studied urban data classification. However, related studies showed poor performance in shallow neural network. Therefore, in this paper the first preprocess voice data and extract feature value. Next, Categorize the voice by entering the feature value into previous sound classification network and proposed neural network. Finally, compare and evaluate classification performance of the two neural networks. The neural network of this paper is organized deeper and wider so that learning is better done. Performance results showed that 84.8 percent of related studies neural networks and 91.4 percent of the proposed neural networks. The proposed neural network was about 6 percent high.

Contents

요약
Abstract
Ⅰ. 서론
Ⅱ. 관련 연구
Ⅲ. 음성 분류
Ⅳ. 성능 평가
Ⅴ. 결론 및 향후 과제
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UCI(KEPA) : I410-ECN-0101-2019-004-000059093