DocumentCode
1909037
Title
A new learning algorithm for minimizing spotting errors
Author
Komori, Takashi ; Katagiri, Shigeru
fYear
1993
fDate
6-9 Sep 1993
Firstpage
333
Lastpage
342
Abstract
A new learning algorithm, called minimum spotting error formalization (MSPE), is proposed for designing a high performance word spotting system. An overall spotting system, comprising word models and decision thresholds, primarily needs to be optimized to minimize all spotting errors; the word models and the thresholds should no longer be separately and heuristically designed. MSPE features a rigorous framework for reducing a spotting error objective in a practical, gradient search-based design scheme. Experimental results in a Japanese consonant spotting task clearly demonstrate the usefulness of the proposed method
Keywords
learning (artificial intelligence); neural nets; search problems; speech recognition; Japanese consonant spotting; MSPE; gradient search-based design scheme; learning algorithm; minimum spotting error formalization; Algorithm design and analysis; Artificial neural networks; Design methodology; Design optimization; Hidden Markov models; Laboratories; Minimization methods; Modems; Speech recognition; Visual perception;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop
Conference_Location
Linthicum Heights, MD
Print_ISBN
0-7803-0928-6
Type
conf
DOI
10.1109/NNSP.1993.471855
Filename
471855
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