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- W1874131957 abstract "The application of the pyramidical multilayered neural net to speaker-independent recognition of isolated Chinese syllables was investigated. The feature extraction algorithm is described. Experiments involving 90 speakers from 25 provinces of China show that accuracies of 82.7% and 87.1% can be achieved, respectively, for ten isolated digits and seven typical syllables, and an over 75% cross-sex recognition rate can be obtained. The results indicate that this neural net technique can be applied to speaker-independent syllable recognition and that its performance is comparable to that of the hidden Markov model method. >" @default.
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- W1874131957 date "2002-12-09" @default.
- W1874131957 modified "2023-09-24" @default.
- W1874131957 title "Speaker-independent syllable recognition by a pyramidical neural net" @default.
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- W1874131957 doi "https://doi.org/10.1109/ijcnn.1991.170712" @default.
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