Metody klasifikace dětí s vývojovou dysfázií založené na analýze narušené řeči

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03145878" target="_blank" >RIV/68407700:21230/08:03145878 - 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

A Classification Method of Children with Developmental Dysphasia Based on Disorder Speech Analysis

Popis výsledku v původním jazyce

This paper focuses on method developed for classifications of the speech with disorders. We are interested in children's neurolog- ical disorder called developmental dysphasia and its in uence on the speech. Described clasification method is based on children's speech sig- nal analysis and allows observing the trend of the speech disorder during therapy. The classification is based on the fact that the disorder has an direct impact on speech production (i.e. movement of vocal tract). Thus, we can measure the trend of the disorders comparing patterns obtained from speech of healthy children to the patterns obtained from children with disorder. Described method is based on cluster analysis of Koho- nen Self-Organizing Maps (KSOMs) trained on speech signals. The main advantage of using artificial neural network is adaptability to specific at- tributes of the signal and tolerance for the noise contained in recordings.

Název v anglickém jazyce

A Classification Method of Children with Developmental Dysphasia Based on Disorder Speech Analysis

Popis výsledku anglicky

This paper focuses on method developed for classifications of the speech with disorders. We are interested in children's neurolog- ical disorder called developmental dysphasia and its in uence on the speech. Described clasification method is based on children's speech sig- nal analysis and allows observing the trend of the speech disorder during therapy. The classification is based on the fact that the disorder has an direct impact on speech production (i.e. movement of vocal tract). Thus, we can measure the trend of the disorders comparing patterns obtained from speech of healthy children to the patterns obtained from children with disorder. Described method is based on cluster analysis of Koho- nen Self-Organizing Maps (KSOMs) trained on speech signals. The main advantage of using artificial neural network is adaptability to specific at- tributes of the signal and tolerance for the noise contained in recordings.

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GD102%2F08%2FH008" target="_blank" >GD102/08/H008: Analýza a modelování biomedicínských a řečových signálů</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2008

Kód důvěrnosti údajů

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

Název statě ve sborníku

Artificial Neural Networks - ICANN 2008

ISBN

978-3-540-87558-1

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

7

Strana od-do

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Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Prague

Datum konání akce

3. 9. 2008

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000259567200085