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A speaker-independent connected digit recognition system concatenating statistically discriminated words

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4 Author(s)
T. Ukita ; Toshiba Kansai Res. Lab., Kobe, Japan ; E. Saito ; T. Nitta ; S. Watanabe

A recognition system for connected digits, which uses a statistical classifier to identify words in speaker-independent continuous speech, is described. The system uses the multiple similarity method, a statistical pattern recognition technique. For evaluating word strings, the system uses a scoring method that is independent of the number of words in the strings. It is derived from the a posteriori probability that a subinterval corresponds to a correct word position, giving a word similarity value. The system evaluates a word string using dynamic programming and a parallel search procedure. Experiments for the contextual effect of the training data set, for validation of the search algorithm, and for a large quantity of unspecified speakers including 40 males and 40 females were performed. For connected digits (unknown word lengths test), the string recognition rates were 90.1%-95.1% for two, three, or four connected digits, where the equivalent word (digit) rates were 97.4%-98.4%

Published in:

IEEE Transactions on Signal Processing  (Volume:40 ,  Issue: 10 )