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Cognitive Computation

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01-09-2010

Phoneme Recognition by Means of a Growing Hierarchical Recurrent Self-Organizing Model Based on Locally Adapting Neighborhood Radii

Authors: Chiraz Jlassi, Najet Arous, Noureddine Ellouze

Published in: Cognitive Computation | Issue 3/2010

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Abstract

This paper presents a tree evolutionary recurrent self-organizing model, based on locally adapting neighborhood radii and multiple prototype vectors named GH-Ad-RSOM. It is a variant of the Growing Hierarchical Self-Organizing Map GHSOM. The proposed GHSOM variant is characterized by a hierarchical model, composed of independent RSOMs (many RSOM), based on a locally adapting neighborhood radii and multiple prototype vectors. The method shows better robustness of GH-Ad-RSOM and high vowel classification rates compared to classic GHSOM and other variant of GHSOM.

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Title: Phoneme Recognition by Means of a Growing Hierarchical Recurrent Self-Organizing Model Based on Locally Adapting Neighborhood Radii
Authors: Chiraz Jlassi
Najet Arous
Noureddine Ellouze
Publication date: 01-09-2010
Publisher: Springer-Verlag
Published in: Cognitive Computation / Issue 3/2010
Print ISSN: 1866-9956
Electronic ISSN: 1866-9964
DOI: https://doi.org/10.1007/s12559-010-9036-5

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