(A) study on the clustering method in speaker independent isolated word recognition = 독립화가 고립단어 인식에 있어서의 Clustering 방법에 관한 연구

In this thesis, we propose a hybrid clustering algorithm called Modified Mutual Nearest Neighborhood(MMNN) clustering, which is aimed at superior performance to other clustering method for speaker independent isolated word recognition. This algorithm, compared to other clustering methods, Unsupervised Without Averaging (UWA) and Chainmap, shows better performance by generating more reliable reference patterns. A new cluster center determination method was devised. Its performance is superior to minimax. And the cluster center determined by this method is one of the real training pattern which saves many computation time.
Advisors
Cho, Jung-WanresearcherMaeng, Seung-Ryeulresearcher조정완researcher맹승렬researcher
Publisher
한국과학기술원
Issue Date
1986
Identifier
65155/325007 / 000841286
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전산학과, 1986.2, [ [ii], 45 p. ]

URI
http://hdl.handle.net/10203/33685
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=65155&flag=t
Appears in Collection
CS-Theses_Master(석사논문)
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