Automatic detection of Parkinson's disease in running speech spoken in three different languages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00237049" target="_blank" >RIV/68407700:21230/16:00237049 - isvavai.cz</a>

Výsledek na webu

<a href="http://scitation.aip.org/content/asa/journal/jasa/139/1/10.1121/1.4939739" target="_blank" >http://scitation.aip.org/content/asa/journal/jasa/139/1/10.1121/1.4939739</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1121/1.4939739" target="_blank" >10.1121/1.4939739</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic detection of Parkinson's disease in running speech spoken in three different languages

Popis výsledku v původním jazyce

The aim of this study is the analysis of continuous speech signals of people with Parkinson's disease (PD) considering recordings in different languages (Spanish, German, and Czech). A method for the characterization of the speech signals, based on the automatic segmentation of utterances into voiced and unvoiced frames, is addressed here. The energy content of the unvoiced sounds is modeled using 12 mel-frequency cepstral coefficients (MFCC) and 25 bands scaled according to the Bark scale. Four speech tasks comprising isolated words, rapid repetition of the syllables /pa/-/ta/-/ka/, sentences, and read texts are evaluated. The method proves to be more accurate than classical approaches in the automatic classification of speech of people with PD and healthy controls (HC). The accuracies range from 85% to 99% depending on the language and the speech task. Cross-language experiments are also performed confirming the robustness and generalization capability of the method, with accuracies ranging from 60% to 99%. This work comprises a step forward for the development of computer aided tools for the automatic assessment of dysarthric speech signals in multiple languages.

Název v anglickém jazyce

Automatic detection of Parkinson's disease in running speech spoken in three different languages

Popis výsledku anglicky

The aim of this study is the analysis of continuous speech signals of people with Parkinson's disease (PD) considering recordings in different languages (Spanish, German, and Czech). A method for the characterization of the speech signals, based on the automatic segmentation of utterances into voiced and unvoiced frames, is addressed here. The energy content of the unvoiced sounds is modeled using 12 mel-frequency cepstral coefficients (MFCC) and 25 bands scaled according to the Bark scale. Four speech tasks comprising isolated words, rapid repetition of the syllables /pa/-/ta/-/ka/, sentences, and read texts are evaluated. The method proves to be more accurate than classical approaches in the automatic classification of speech of people with PD and healthy controls (HC). The accuracies range from 85% to 99% depending on the language and the speech task. Cross-language experiments are also performed confirming the robustness and generalization capability of the method, with accuracies ranging from 60% to 99%. This work comprises a step forward for the development of computer aided tools for the automatic assessment of dysarthric speech signals in multiple languages.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

—

Projekt

—

Návaznosti

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 periodika

JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA

ISSN

0001-4966

e-ISSN

—

Svazek periodika

139

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

20

Strana od-do

481-500

Kód UT WoS článku

000379568000044

EID výsledku v databázi Scopus

2-s2.0-84956810479