An Automatic Diagnosis and Assessment of Dysarthric Speech using Speech Disorder Specific Prosodic Features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU120009" target="_blank" >RIV/00216305:26220/16:PU120009 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7760933" target="_blank" >https://ieeexplore.ieee.org/document/7760933</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP.2016.7760933" target="_blank" >10.1109/TSP.2016.7760933</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Automatic Diagnosis and Assessment of Dysarthric Speech using Speech Disorder Specific Prosodic Features

Popis výsledku v původním jazyce

To diagnose and classify the dysarthria speech, speech language pathologist (SLP) conduct a listening test. On the basis of the scores given by listeners the dysarthria is diagnosed and assessed. The above mentioned method is costly, time consuming and not very accurate. Unlike the traditional method, this research proposes an automatic diagnosis and assessment of dysarthria. The aim of this paper is to diagnose and classify the severity of dysarthria. The speech disorder specific prosodic features are selected by using genetic algorithm. The diagnosis and assessment of dysarthria speech is done by support vector machines. During diagnosis the classification accuracy of 98% has been achieved. And 87% of the dysarthria speech utterances are correctly classified. The standard UASPEECH database has been used in this work.

Název v anglickém jazyce

An Automatic Diagnosis and Assessment of Dysarthric Speech using Speech Disorder Specific Prosodic Features

Popis výsledku anglicky

To diagnose and classify the dysarthria speech, speech language pathologist (SLP) conduct a listening test. On the basis of the scores given by listeners the dysarthria is diagnosed and assessed. The above mentioned method is costly, time consuming and not very accurate. Unlike the traditional method, this research proposes an automatic diagnosis and assessment of dysarthria. The aim of this paper is to diagnose and classify the severity of dysarthria. The speech disorder specific prosodic features are selected by using genetic algorithm. The diagnosis and assessment of dysarthria speech is done by support vector machines. During diagnosis the classification accuracy of 98% has been achieved. And 87% of the dysarthria speech utterances are correctly classified. The standard UASPEECH database has been used in this work.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

2016 39th International Conference on Telecommunications and Signal Processing (TSP)

ISBN

978-1-5090-1287-9

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

515-518

Název nakladatele

Neuveden

Místo vydání

Vienna, Austria

Místo konání akce

Vídeň

Datum konání akce

27. 6. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000390164000112