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 University--MIT Division of Health Sciences and Technology | |
dc.identifier.oclc | 792946210 | en_US |