Fast fuzzy clustering approach for real time speaker identification with feature projection and dimension reduction특정 돌출과 차원 감소를 가진 실 시간 스피커를 확인하기 위한 빠른 퍼지 클러스터링 접근SC SE

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Speaker identification applications are the highly commercialized during the speaker recognition and voice biometrics applications which experienced high interests and an increasing market during the last few years. Like other applications it has been experiencing an increasing market and investor interest [1]. However, it is still an open area for research. In this thesis we considered creating a real-time speaker identification system as an optimization problem. However, many researches proceeded in this direction. In our proposed system, pattern recognition techniques like clustering and p-tree search were used to reduce the number of calculations and database comparisons in order to speed up the identification process while entropy and principal component analysis were applied to reduce the dimensionality of data and thus reducing data storage size. These modifications allow the user making trade off between accuracy, response time and resource usage based on the usage case of action. Here, we took a newly proposed technique proposed by Karpov [33] to compare our technique with it. The results, when testing both systems on ELSDSR voices database, show that the newly proposed technique is better than the old proposed one in terms of timing, memory usage and accuracy.
Advisors
Lee, Dan-Hyungresearcher이단형researcher
Description
한국정보통신대학교 : 공학부,
Publisher
한국정보통신대학교
Issue Date
2008
Identifier
393064/225023 / 020064690
Language
eng
Description

학위논문(석사) - 한국정보통신대학교 : 공학부, 2008.8, [ iv, 81 p. ]

Keywords

Fast Fuzzy C-mean; Principal Components Analysis; Entropy; Dimension Reduction; Real Time Speaker Identification; Vector Quantization; 벡터 양자화; 빠른 퍼지 씨-민; 주요 성분 분석; 엔트로피; 차원 감소; 실 시간 스피커 확인

URI
http://hdl.handle.net/10203/55046
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=393064&flag=dissertation
Appears in Collection
School of Engineering-Theses_Master(공학부 석사논문)
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