Speech Recognition with Fuzzy Neural Network for Discrete Words

In this paper we study the feasibility of speech recognition with fuzzy neural Networks for discrete words, dependent or not dependent on speaker. Different Technical methods are used for speech recognition. Most of these methods are based on transfiguration of the speech signals for phonemes and syllables of the words. We use the expression "word Recognition" (because in our proposed method there is no need to catch the phonemes of words.). In our proposed method, Kohonen and LVQ networks are used for compaction and learning the data and then the output is sent to a fuzzy system and a neuro fuzzy system for classifying the conclusion. The experimental results show good precisions. The recognition precision of our proposed method with fuzzy conclusion is 95 percent and with ANFIS conclusion is 96 percent for good data and for all data is 58 percent.