Self-Organizing Maps For Identifying Impaired Speech

Self-Organizing Maps For Identifying Impaired Speech

This paper presents a method of identifying heavily impaired pronunciations of 'r' consonant in Romanian language using Kohonen neural networks. The study focused on words that contain 'r' as the first letter and used signals recorded mainly from children, as mispronunciations...

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Bibliographic Details
Main Authors: GRIGORE, O., VELICAN, V.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2011-08-01
Series:Advances in Electrical and Computer Engineering
Subjects:
speech processing
impaired speech evaluation
self-organizing maps
Online Access:http://dx.doi.org/10.4316/AECE.2011.03007
Description
Summary:This paper presents a method of identifying heavily impaired pronunciations of 'r' consonant in Romanian language using Kohonen neural networks. The study focused on words that contain 'r' as the first letter and used signals recorded mainly from children, as mispronunciations occur most of the time at young age persons. Parameters of the alternating component of each speech sample's envelope are used as feature vectors in the classification stage.
ISSN:1582-7445
1844-7600

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