Neuro-fuzzy Models for Speech Pattern Recognition in Romanian Language
نویسندگان
چکیده
In this paper are presented results obtained in a vowel recognition task applying fuzzy neural networks. The vowels, uttered from 10 speakers each in 1000 different contexts are recognized using as features the first three formant frequencies. The results obtained in this case show that fuzzyfication process improves the recognition rate of the classical variants. The paper is organized in 6 chapters: after an introduction (1), the feature extraction (2) is presented. The two fuzzy neural networks: the fuzzy multilayer perceptron (2) and the fuzzy Kohonen map (3) used for recognition are given. Conclusions about the obtained results with future plans (4) and a reference list (5) close the paper.
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