DocumentCode :
2616005
Title :
Fuzzy variants of hard classification rules for speech pattern recognition in Romanian language
Author :
Gavat, Inge ; Grigore, Ovidiu ; Zirra, Matei ; Cula, Oana
Author_Institution :
Fac. of Electron. & Telecommun., Politehnica Univ. of Bucharest, Romania
fYear :
1997
fDate :
21-24 Sep 1997
Firstpage :
172
Lastpage :
176
Abstract :
The paper presents results obtained in a vowel recognition task applying unsupervised and supervised fuzzy algorithms and fuzzy neural networks. The vowels, uttered from 10 speakers each in 1000 different contexts are recognized using as features the first three formant frequencies. Feature extraction is presented and two fuzzy algorithms, fuzzy ISODATA and fuzzy k-NN, and the fuzzy multilayer perceptron neural network used for recognition are given. Conclusions about the obtained results with future plans and a reference list close the paper
Keywords :
feedforward neural nets; fuzzy neural nets; learning systems; multilayer perceptrons; pattern classification; speech recognition; Romanian language; feature extraction; formant frequencies; fuzzy ISODATA; fuzzy hard classification rules; fuzzy k-NN; fuzzy multilayer perceptron neural network; fuzzy neural networks; speakers; speech pattern recognition; supervised fuzzy algorithms; unsupervised fuzzy algorithms; vowel recognition task; Cepstrum; Clustering algorithms; Electronic mail; Frequency; Fuzzy sets; Histograms; Natural languages; Pattern recognition; Prototypes; Speech processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-4078-7
Type :
conf
DOI :
10.1109/NAFIPS.1997.624031
Filename :
624031
Link To Document :
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