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Online control of articulation based on auditory feedback in normal Speech and stuttering : behavioral and modeling studies

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dc.contributor.advisor Frank H. Guenther and Joseph S. Perkell. en_US
dc.contributor.author Cai, Shanqing en_US
dc.contributor.other Harvard--MIT Program in Health Sciences and Technology. en_US
dc.date.accessioned 2012-05-15T21:14:27Z
dc.date.available 2012-05-15T21:14:27Z
dc.date.copyright 2011 en_US
dc.date.issued 2012 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/70812
dc.description Thesis (Ph. D.)--Harvard-MIT Program in Health Sciences and Technology, February 2012. en_US
dc.description "February, 2012." Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 185-209). en_US
dc.description.abstract Articulation of multisyllabic speech requires a high degree of accuracy in controlling the spatial (positional) and the temporal parameters of articulatory movements. In stuttering, a disorder of speech fluency, failures to meet these control requirements occur frequently, leading to dysfluencies such as sound repetitions and prolongations. Currently, little is known about the sensorimotor mechanisms underlying the control of multisyllabic articulation and how they break down in stuttering. This dissertation is focused on the interaction between multisyllabic articulation and auditory feedback (AF), the perception of one's own speech sounds during speech production, which has been shown previously to play important roles in quasi-static articulations as well as in the mechanisms of stuttering. To investigate this topic empirically, we developed a digital signal processing platform for introducing flexible online perturbations of time-varying formants in speakers' AF during speech production. This platform was in a series of perturbation experiments, in which we aimed separately at elucidating the role of AF in controlling the spatial and temporal parameters of multisyllabic articulation. Under these perturbations of AF, normal subjects showed small but significant and specific online adjustments in the spatial and temporal parameters of articulation, which provided first evidence for a role of AF in the online fine-tuning of articulatory trajectories. To model and explain these findings, we designed and tested sqDIVA, a computational model for the sensory feedback-based control of speech movement timing. Test results indicated that this new model accurately accounted for the spatiotemporal compensation patterns observed in the perturbation experiments. In addition, we investigated empirically how the AF-based online speech motor control differed between people who stutter (PWS) and normal speakers. The PWS group showed compensatory responses significantly smaller in magnitude and slower in onset compared to the control subjects' responses. This under-compensation to AF perturbation was observed for both quasi-static vowels and multisyllabic speech, and for both the spatial and temporal control of articulation. This abnormal sensorimotor performance supports the hypothesis that stuttering involves deficits in the rapid internal transformations between the auditory and motor domains, with important implications for the neural basis of this disorder. en_US
dc.description.statementofresponsibility by Shanqing Cai. en_US
dc.format.extent 209 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Harvard--MIT Program in Health Sciences and Technology. en_US
dc.title Online control of articulation based on auditory feedback in normal Speech and stuttering : behavioral and modeling studies en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Harvard--MIT Program in Health Sciences and Technology. en_US
dc.identifier.oclc 792946210 en_US


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