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This paper presents a novel approach to speech recognition using fuzzy modeling. The task begins with conversion of speech spectrogram into a linguistic description based on arbitrary colors and lengths. While phonemes are also described using these fuzzy measures, and recognition is done by normal fuzzy reasoning, a genetic algorithm optimizes phoneme definitions so that to classify samples into correct phonemes. The method is tested over a standard speech data base and the results are presented.