Prosodic analysis of neutral, stress-modified and rhymed speech in patients with Parkinson's disease. Issue 127 (April 2016)

• Record Type: Journal Article
• Authors: Galaz, Zoltan; Mekyska, Jiri; Mzourek, Zdenek; Smekal, Zdenek; Rektorova, Irena; Eliasova, Ilona; Kostalova, Milena; Mrackova, Martina; Berankova, Dagmar
• Is Part Of: Computer methods and programs in biomedicine. Issue 127(2016)
• Page Start: 301
• Page End: 317
• Publication Date: 2016-04
• Subjects: Parkinson's disease -- Hypokinetic dysarthria -- Feature selection -- Random forests -- Dysprosody; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.12.011
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract : Highlights: We analysed neutral, stress-modified and rhymed speech in Parkinson's disease. We proposed quantitative prosodic analysis of poem recitation task. We showed rhythmical demands improve identification of hypokinetic dysarthria. We introduced a concept of permutation test in dysarthric speech analysis. Abstract: Background and objective: Hypokinetic dysarthria (HD) is a frequent speech disorder associated with idiopathic Parkinson's disease (PD). It affects all dimensions of speech production. One of the most common features of HD is dysprosody that is characterized by alterations of rhythm and speech rate, flat speech melody, and impairment of speech intensity control. Dysprosody has a detrimental impact on speech naturalness and intelligibility. Methods: This paper deals with quantitative prosodic analysis of neutral, stress-modified and rhymed speech in patients with PD. The analysis of prosody is based on quantification of monopitch, monoloudness, and speech rate abnormalities. Experimental dataset consists of 98 patients with PD and 51 healthy speakers. For the purpose of HD identification, sequential floating feature selection algorithm and random forests classifier is used. In this paper, we also introduce a concept of permutation test applied in the field of acoustic analysis of dysarthric speech. Results: Prosodic features obtained from stress-modified reading task provided higher classification accuracies compared to the ones extracted from reading task with neutral emotion demonstrating the importance of stress in speech prosody. Features calculated from poem recitation task outperformed both reading tasks in the case of gender-undifferentiated analysis showing that rhythmical demands can in general lead to more precise identification of HD. Additionally, some gender-related patterns of dysprosody has been observed. Conclusions: This paper confirms reduced variation of fundamental frequency in PD patients with HD. Interestingly, increased variability of speech intensity compared to healthy speakers has been detected. Regarding speech rate disturbances, our results does not report any particular pattern. We conclude further development of prosodic features quantifying the relationship between monopitch, monoloudness and speech rate disruptions in HD can have a great potential in future PD analysis.