Speech modelling using phoneme segmentation and modified weighted levenshtein distance

A method of choosing a word hypothesis from a dictionary of a speech recognition system is presented. The method applies a modified weighted Levenshtein distance for better accuracy. The distance is counted between phonetic transcriptions of a string of phonemes received from a classifier and of a dictionary. It allows efficient conducting of speech classifying task.