Data Mining of Children´s Speech by Growing Hierarchical Self-Organizing Map

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A00126098" target="_blank" >RIV/68407700:21230/06:00126098 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Data Mining of Children´s Speech by Growing Hierarchical Self-Organizing Map

Popis výsledku v původním jazyce

The subject of the contribution is one of application of KSOM in medical research. It behaves about of parts of the project finding connectivity between neurological disorders of children - developmental dysphasia and assessment of the degree of perception and impairment of speech. Our research is based on classification solved by SSOM with using phonetics knowledge. We use this approach for neural network ability to recognize relevant and irrelevant information about speech and minor noise dependence.The SSOM combines aspects of a vector quantization method with a topology-preserving ordering of the quantization vectors. Children speech database is away complemented. It must bee structed according to age and gender. The submitted maps trained by input data of 6 years old healthy children were compared with the input data of 6 patients observed befor and after first portion medical therapy. The assumed difference in Recognition Rate between both records was proved true.

Název v anglickém jazyce

Data Mining of Children´s Speech by Growing Hierarchical Self-Organizing Map

Popis výsledku anglicky

The subject of the contribution is one of application of KSOM in medical research. It behaves about of parts of the project finding connectivity between neurological disorders of children - developmental dysphasia and assessment of the degree of perception and impairment of speech. Our research is based on classification solved by SSOM with using phonetics knowledge. We use this approach for neural network ability to recognize relevant and irrelevant information about speech and minor noise dependence.The SSOM combines aspects of a vector quantization method with a topology-preserving ordering of the quantization vectors. Children speech database is away complemented. It must bee structed according to age and gender. The submitted maps trained by input data of 6 years old healthy children were compared with the input data of 6 patients observed befor and after first portion medical therapy. The assumed difference in Recognition Rate between both records was proved true.

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/NR8287" target="_blank" >NR8287: Počítačová analýza řečového projevu a celonočních EEG záznamů u dětí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2006

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Digital Technologies 2006 - 3rd International Workshop

ISBN

80-8070-637-9

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

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Název nakladatele

Žilinská universita, Elektrotechnická fakulta

Místo vydání

Žilina

Místo konání akce

Žilina

Datum konání akce

1. 12. 2006

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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