Automatic detection of Parkinson's disease in running speech spoken in three different languages - Orozco-Arroyave, J R; Hönig, F; Arias-Londoño, J D; Vargas-Bonilla, J F; Daqrouq, K; Skodda, S; Rusz, J; Nöth, E (The Journal of the Acoustical Society of America, 2016)
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 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. 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.
Keywords: Recognition, Psychology; dospělí; Španělsko; Germany; Female; rozpoznávání (psychologie); Parkinsonova nemoc; Spain; Phonetics; Adult; ženské pohlaví; lidé; Area Under Curve; Německo; jazyk (prostředek komunikace); Aged, 80 and over; Speech Acoustics; Humans; Male; Aged; Czech Republic; Reading; Language; Česká republika; Speech; akustika řeči; lidé středního věku; plocha pod křivkou; senioři nad 80 let; senioři; mužské pohlaví; čtení; Middle Aged; řeč; Parkinson Disease; fonetika