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Fuzzy variants of hard classification rules for speech pattern recognition in Romanian language

机译:罗马尼语语言语言模式识别的硬分类规则模糊变体

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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.
机译:本文提出了在应用无监督和监督模糊算法和模糊神经网络的元音识别任务中获得的结果。从10个扬声器中发出的元音,每个扬声器中的1000个不同的上下文都是使用前三种中文体频率的特征来识别的。提取特征提取,并给出了两个模糊算法,模糊isodata和模糊K-Nn,以及用于识别的模糊多层的Perceptron神经网络。结论与未来计划和参考文档的结果接近纸张。

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