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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
In modern society, speech recognition technology is emerging as an important technology for identification in electronic commerce, forensics, law enforcement, and other systems. In this study, we aim to develop an age classification algorithm for extracting only MFCC(Mel Frequency Cepstral Coefficient) expressing the characteristics of speech in Korean and applying it to deep learning technology. The algorithm for extracting the 13th order MFCC from Korean data and constructing a data set, and using the artificial intelligence algorithm, deep artificial neural network, to classify males in their 20s, 30s, and 50s, and females in their 20s, 40s, and 50s. finally, our model confirmed the classification accuracy of 78.6% and 71.9% for males and females, respectively.
목차
등록된 정보가 없습니다.
참고문헌 (14)
참고문헌 신청
J.H.L. Hansen / 2015 / Speaker recognition by machines and humans: A tutorial review / IEEE Signal Proc. Mag. 32(6):74~99
Schuller, B. / 2010 / The INTERSPEECH 2010 Paralinguistic Challenge / Proc. INTERSPEECH 2010, Makuhari, Japan :2794~2797
M. Li / 2013 / Automatic speaker age and gender recognition using acoustic and prosodic level information fusion / Computer Speech & Language 27(1):151~167
Phuoc Nguyen / 2010 / Fuzzy support vector machines for age and gender classification / NTERSPEECH 2010 :2806~2809
강우현 / 2015 / I-벡터 특징을 이용하는 NN 기반의 화자 연령 분류 / 한국통신학회 학술대회논문집 :589~590
Schuller, B. / 2010 / The INTERSPEECH 2010 Paralinguistic Challenge / Proc. INTERSPEECH 2010, Makuhari, Japan :2794~2797
M. Li / 2013 / Automatic speaker age and gender recognition using acoustic and prosodic level information fusion / Computer Speech & Language 27(1):151~167
Phuoc Nguyen / 2010 / Fuzzy support vector machines for age and gender classification / NTERSPEECH 2010 :2806~2809
강우현 / 2015 / I-벡터 특징을 이용하는 NN 기반의 화자 연령 분류 / 한국통신학회 학술대회논문집 :589~590
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