2026-09-20T08:03:03Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/707892022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Joseph S. Perkell.
Cai, Shanqing
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2012-05-15T21:12:37Z
2012-05-15T21:12:37Z
2012
2012
http://hdl.handle.net/1721.1/70789
792751615
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 61-65).
This thesis aims at elucidating the role of auditory feedback in the learning and planning of complex articulatory gestures in time-varying phonemes. To this end, we studied native Mandarin speakers' responses to perturbations of their auditory feedback of the first and second formant trajectories during the production of the Mandarin triphthong /iau/. On the group level, subjects adaptively adjusted their productions to partially compensate for the perturbations in auditory feedback under both the F1 and F2 perturbations. But considerable between-individual variation existed. The result indicate that auditory feedback-based learning and control of speech movements is not restricted to quasi-static gestures in monophthongs as found in previous studies, but also extends to time-varying gestures. To probe the internal structure of the mechanisms of auditory-motor transformations in speech, we tested the pattern of generalization of the adaptation trained on the triphthong /iau/ to other vowels with different spatial and temporal characteristics in the same language. A broad but weak and decaying pattern of generalization was observed under the F1 perturbation; the strength of the generalization diminished with increasing dissimilarity from /iau/. No significant transfer of adaptation was found under the perturbation of F2. The details and implications of the pattern of generalization are examined and discussed in light of previous sensorimotor adaptation studies of speech and limb motor control and a neurocomputational model of speech motor control.
by Shanqing Cai.
S.M.
65 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Adaptive auditory-motor control of the time-varying formant trajectories in vowels and its patterns of generalization
Thesis
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<Abstract>This thesis aims at elucidating the role of auditory feedback in the learning and planning of complex articulatory gestures in time-varying phonemes. To this end, we studied native Mandarin speakers' responses to perturbations of their auditory feedback of the first and second formant trajectories during the production of the Mandarin triphthong /iau/. On the group level, subjects adaptively adjusted their productions to partially compensate for the perturbations in auditory feedback under both the F1 and F2 perturbations. But considerable between-individual variation existed. The result indicate that auditory feedback-based learning and control of speech movements is not restricted to quasi-static gestures in monophthongs as found in previous studies, but also extends to time-varying gestures. To probe the internal structure of the mechanisms of auditory-motor transformations in speech, we tested the pattern of generalization of the adaptation trained on the triphthong /iau/ to other vowels with different spatial and temporal characteristics in the same language. A broad but weak and decaying pattern of generalization was observed under the F1 perturbation; the strength of the generalization diminished with increasing dissimilarity from /iau/. No significant transfer of adaptation was found under the perturbation of F2. The details and implications of the pattern of generalization are examined and discussed in light of previous sensorimotor adaptation studies of speech and limb motor control and a neurocomputational model of speech motor control.</Abstract>
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