Title :
A new learning algorithm for minimizing spotting errors
Author :
Komori, Takashi ; Katagiri, Shigeru
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;
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
DOI :
10.1109/NNSP.1993.471855