DocumentCode :
2175567
Title :
Fuzzy-based clustering of speech recognition database
Author :
Garjdos, S. ; Lörincz, Attila
Author_Institution :
Dept. if Telecommun. & Telematics, Budapest Tech. Univ., Hungary
Volume :
3
fYear :
1998
fDate :
11-14 Oct 1998
Firstpage :
2744
Abstract :
Algorithms have been proposed and experimentally tested for word recognition as part of a speech recognition system. These algorithms are based on a fuzzy model relying on the output signal of a recogniser of phoneme level. The recognition is carried out in a clustered database of words containing both the pronounced and the written forms of words as well. The clusters are selected on the basis of word schemes that characterise all of the words in a cluster and discriminate different clusters. Experiments have been made to prove the effectiveness of the proposed algorithms. The obtained improvement in speed was in our test approximately 30 times higher compared to a full search, without significant degradation of word recognition ratio
Keywords :
fuzzy set theory; pattern clustering; speech recognition; clustered database; fuzzy model; fuzzy-based clustering; phoneme level; speech recognition database; speech recognition system; word recognition; word schemes; Clustering algorithms; Databases; Degradation; Dictionaries; Pattern recognition; Sea measurements; Speech recognition; System testing; Telematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
ISSN :
1062-922X
Print_ISBN :
0-7803-4778-1
Type :
conf
DOI :
10.1109/ICSMC.1998.725076
Filename :
725076
Link To Document :
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