Acoustic features to characterize sentence accent production in dysarthric speech. (March 2020)

• Record Type: Journal Article
• Authors: Mendoza Ramos, Viviana; Kairuz Hernandez-Diaz, Hector A.; Hernandez-Diaz Huici, Maria E.; Martens, Heidi; Van Nuffelen, Gwen; De Bodt, Marc
• Is Part Of: Biomedical signal processing and control. Volume 57(2020)
• Publication Date: 2020-03
• Subjects: Sentence accent -- Dysarthria -- Acoustic features -- Prosody -- Dutch; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.101750
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: An objective acoustic analysis of speech was performed with an automatic algorithm. New relevant features correlated with sentence accent in native speakers of Dutch were detected. Automatic classification between accented and unaccented syllables shows a high reliability using the selected feature sets. The introduced features enable a better understanding and description of different accent strategies between healthy speakers and speakers with dysarthria. This knowledge may allow therapists to develop and adjust methods for the rehabilitation of sentence accent. Abstract: This study investigated acoustic features and prosodic strategies used by both healthy speakers and speakers with dysarthria, to produce a perceptually-detectable sentence accent. Accordingly, 80 adult speakers (50 with a speech impairment) were asked to produce 3 pairs of sentences with different accent positions. All speech samples were perceptually judged by three experts, and were acoustically analyzed. The fundamental frequency, intensity, and duration were not only analyzed within the syllable, but also in contrast with the previous syllable, and in contrast with the entire sentence. These features were used as input for a linear discriminant analysis. This newly-developed acoustic approach reveals that healthy speakers mainly rely on the following features to produce a perceptually-detectable accent: a change in frequency within the target syllable, with a simultaneous increase of intensity and contrast in the frequency between the target syllable and the previous syllable. Speakers with dysarthria mainly use the contrast in frequency and intensity between the target syllable and the previous syllable, rather than the contrasting with the rest of the sentence. They also use durational parameters as an element in prosodic accent production. Although both groups use some common features, they differ significantly (p < 0.01) in the way they realize accent production. The results of this study show that sentence accent production in dysarthric speech can be adequately described by a set of acoustic features. Until now, such description in the literature was primarily based on perceptual evaluations. The current approach may assist in objective assessments and more appropriate therapy methods.