Voiced/unvoiced transitions in speech as a potential bio-marker to detect Parkinson's disease

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00239926" target="_blank" >RIV/68407700:21230/15:00239926 - isvavai.cz</a>

Výsledek na webu

<a href="https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2015/Orozco-Arroyave15-VTI.pdf" target="_blank" >https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2015/Orozco-Arroyave15-VTI.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Voiced/unvoiced transitions in speech as a potential bio-marker to detect Parkinson's disease

Popis výsledku v původním jazyce

Several studies have addressed the automatic classification of speakers with Parkinson's disease (PD) and healthy controls (HC). Most of the studies are based on speech recordings of sustained vowels, isolated words, and single sentences. Only few investigations have considered read texts and/or spontaneous speech. This paper addresses two main questions still open regarding the automatic analysis speech in patients with PD, (a) "Is it possible to classify PD patients and HC through running speech signals in multiple languages", and (b) "where is the information to discriminate between speech recordings of PD patients and HC" In this paper speech recordings of read texts and monologues spoken in three different languages are considered. The energy content of the borders between voiced and unvoiced sounds is modeled. According to the results with read texts it is possible to achieve accuracies ranging from 91% to 98% depending on the language. With respect to the results on monologues,

Název v anglickém jazyce

Voiced/unvoiced transitions in speech as a potential bio-marker to detect Parkinson's disease

Popis výsledku anglicky

Several studies have addressed the automatic classification of speakers with Parkinson's disease (PD) and healthy controls (HC). Most of the studies are based on speech recordings of sustained vowels, isolated words, and single sentences. Only few investigations have considered read texts and/or spontaneous speech. This paper addresses two main questions still open regarding the automatic analysis speech in patients with PD, (a) "Is it possible to classify PD patients and HC through running speech signals in multiple languages", and (b) "where is the information to discriminate between speech recordings of PD patients and HC" In this paper speech recordings of read texts and monologues spoken in three different languages are considered. The energy content of the borders between voiced and unvoiced sounds is modeled. According to the results with read texts it is possible to achieve accuracies ranging from 91% to 98% depending on the language. With respect to the results on monologues,

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

INTERSPEECH 2015

ISBN

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ISSN

2308-457X

e-ISSN

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Počet stran výsledku

5

Strana od-do

95-99

Název nakladatele

ISCA - International Speech Communication Association

Místo vydání

Bochum

Místo konání akce

Dresden

Datum konání akce

6. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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