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Description
Everyday speech communication typically takes place face-to-face. Accordingly, the task of perceiving speech is a multisensory phenomenon involving both auditory and visual information. The current investigation examines how visual information influences recognition of dysarthric speech. It also explores where the influence of visual information is dependent upon age. Forty adults

Everyday speech communication typically takes place face-to-face. Accordingly, the task of perceiving speech is a multisensory phenomenon involving both auditory and visual information. The current investigation examines how visual information influences recognition of dysarthric speech. It also explores where the influence of visual information is dependent upon age. Forty adults participated in the study that measured intelligibility (percent words correct) of dysarthric speech in auditory versus audiovisual conditions. Participants were then separated into two groups: older adults (age range 47 to 68) and young adults (age range 19 to 36) to examine the influence of age. Findings revealed that all participants, regardless of age, improved their ability to recognize dysarthric speech when visual speech was added to the auditory signal. The magnitude of this benefit, however, was greater for older adults when compared with younger adults. These results inform our understanding of how visual speech information influences understanding of dysarthric speech.
ContributorsFall, Elizabeth (Author) / Liss, Julie (Thesis advisor) / Berisha, Visar (Committee member) / Gray, Shelley (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Often termed the "gold standard" in the differential diagnosis of dysarthria, the etiology-based Mayo Clinic classification approach has been used nearly exclusively by clinicians since the early 1970s. However, the current descriptive method results in a distinct overlap of perceptual features across various etiologies, thus limiting the clinical utility of

Often termed the "gold standard" in the differential diagnosis of dysarthria, the etiology-based Mayo Clinic classification approach has been used nearly exclusively by clinicians since the early 1970s. However, the current descriptive method results in a distinct overlap of perceptual features across various etiologies, thus limiting the clinical utility of such a system for differential diagnosis. Acoustic analysis may provide a more objective measure for improvement in overall reliability (Guerra & Lovely, 2003) of classification. The following paper investigates the potential use of a taxonomical approach to dysarthria. The purpose of this study was to identify a set of acoustic correlates of perceptual dimensions used to group similarly sounding speakers with dysarthria, irrespective of disease etiology. The present study utilized a free classification auditory perceptual task in order to identify a set of salient speech characteristics displayed by speakers with varying dysarthria types and perceived by listeners, which was then analyzed using multidimensional scaling (MDS), correlation analysis, and cluster analysis. In addition, discriminant function analysis (DFA) was conducted to establish the feasibility of using the dimensions underlying perceptual similarity in dysarthria to classify speakers into both listener-derived clusters and etiology-based categories. The following hypothesis was identified: Because of the presumed predictive link between the acoustic correlates and listener-derived clusters, the DFA classification results should resemble the perceptual clusters more closely than the etiology-based (Mayo System) classifications. Results of the present investigation's MDS revealed three dimensions, which were significantly correlated with 1) metrics capturing rate and rhythm, 2) intelligibility, and 3) all of the long-term average spectrum metrics in the 8000 Hz band, which has been linked to degree of phonemic distinctiveness (Utianski et al., February 2012). A qualitative examination of listener notes supported the MDS and correlation results, with listeners overwhelmingly making reference to speaking rate/rhythm, intelligibility, and articulatory precision while participating in the free classification task. Additionally, acoustic correlates revealed by the MDS and subjected to DFA indeed predicted listener group classification. These results beget acoustic measurement as representative of listener perception, and represent the first phase in supporting the use of a perceptually relevant taxonomy of dysarthria.
ContributorsNorton, Rebecca (Author) / Liss, Julie (Thesis advisor) / Azuma, Tamiko (Committee member) / Ingram, David (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The activation of the primary motor cortex (M1) is common in speech perception tasks that involve difficult listening conditions. Although the challenge of recognizing and discriminating non-native speech sounds appears to be an instantiation of listening under difficult circumstances, it is still unknown if M1 recruitment is facilitatory of second

The activation of the primary motor cortex (M1) is common in speech perception tasks that involve difficult listening conditions. Although the challenge of recognizing and discriminating non-native speech sounds appears to be an instantiation of listening under difficult circumstances, it is still unknown if M1 recruitment is facilitatory of second language speech perception. The purpose of this study was to investigate the role of M1 associated with speech motor centers in processing acoustic inputs in the native (L1) and second language (L2), using repetitive Transcranial Magnetic Stimulation (rTMS) to selectively alter neural activity in M1. Thirty-six healthy English/Spanish bilingual subjects participated in the experiment. The performance on a listening word-to-picture matching task was measured before and after real- and sham-rTMS to the orbicularis oris (lip muscle) associated M1. Vowel Space Area (VSA) obtained from recordings of participants reading a passage in L2 before and after real-rTMS, was calculated to determine its utility as an rTMS aftereffect measure. There was high variability in the aftereffect of the rTMS protocol to the lip muscle among the participants. Approximately 50% of participants showed an inhibitory effect of rTMS, evidenced by smaller motor evoked potentials (MEPs) area, whereas the other 50% had a facilitatory effect, with larger MEPs. This suggests that rTMS has a complex influence on M1 excitability, and relying on grand-average results can obscure important individual differences in rTMS physiological and functional outcomes. Evidence of motor support to word recognition in the L2 was found. Participants showing an inhibitory aftereffect of rTMS on M1 produced slower and less accurate responses in the L2 task, whereas those showing a facilitatory aftereffect of rTMS on M1 produced more accurate responses in L2. In contrast, no effect of rTMS was found on the L1, where accuracy and speed were very similar after sham- and real-rTMS. The L2 VSA measure was indicative of the aftereffect of rTMS to M1 associated with speech production, supporting its utility as an rTMS aftereffect measure. This result revealed an interesting and novel relation between cerebral motor cortex activation and speech measures.
ContributorsBarragan, Beatriz (Author) / Liss, Julie (Thesis advisor) / Berisha, Visar (Committee member) / Rogalsky, Corianne (Committee member) / Restrepo, Adelaida (Committee member) / Arizona State University (Publisher)
Created2018
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Description
In this study, the Bark transform and Lobanov method were used to normalize vowel formants in speech produced by persons with dysarthria. The computer classification accuracy of these normalized data were then compared to the results of human perceptual classification accuracy of the actual vowels. These results were then analyzed

In this study, the Bark transform and Lobanov method were used to normalize vowel formants in speech produced by persons with dysarthria. The computer classification accuracy of these normalized data were then compared to the results of human perceptual classification accuracy of the actual vowels. These results were then analyzed to determine if these techniques correlated with the human data.
ContributorsJones, Hanna Vanessa (Author) / Liss, Julie (Thesis director) / Dorman, Michael (Committee member) / Borrie, Stephanie (Committee member) / Barrett, The Honors College (Contributor) / Department of Speech and Hearing Science (Contributor) / Department of English (Contributor) / Speech and Hearing Science (Contributor)
Created2013-05