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 d...

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Bibliographic Details
Main Authors: Ziólko, B, Gałka, J, Skurzok, D
Format: Conference Proceeding
Language:English
Subjects:
Acoustics
Conferences
Dictionaries
Hidden Markov models
Speech
Speech processing
Speech recognition
Online Access:Request full text
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Summary: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.
DOI:10.1109/ICALIP.2010.5685072