On the use of neural networks and fuzzy logic in speech recognition
Amano, Aritsuka, Hataoka, Ichikawa · 1989
A rule-based phoneme recognition method is proposed. This method uses neural networks for acoustic feature detection and fuzzy logic for the decision procedure. Rules for phoneme recognition are prepared for each pair of phonemes (pair-discrimination rules). Recognition experiments were performed using Japanese city names uttered by two male speakers. About 80% of the errors occurring in conventional template matching, which the discrimination rules were designed to recover, were in fact recovered (an improvement in recognition rate of 4.0 to 8.0%). This confirms the effectiveness of the proposed method.>