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Previous studies have shown that experimentally implemented formant perturbations result in production of compensatory responses in the opposite direction of the perturbations. In this study, we investigated how participants adapt to a) auditory perturbations that shift formants to a specific point in the vowel space and hence remove variability of

Previous studies have shown that experimentally implemented formant perturbations result in production of compensatory responses in the opposite direction of the perturbations. In this study, we investigated how participants adapt to a) auditory perturbations that shift formants to a specific point in the vowel space and hence remove variability of formants (focused perturbations), and b) auditory perturbations that preserve the natural variability of formants (uniform perturbations). We examined whether the degree of adaptation to focused perturbations was different from adaptation to uniform adaptations. We found that adaptation magnitude of the first formant (F1) was smaller in response to focused perturbations. However, F1 adaptation was initially moved in the same direction as the perturbation, and after several trials the F1 adaptation changed its course toward the opposite direction of the perturbation. We also found that adaptation of the second formant (F2) was smaller in response to focused perturbations than F2 responses to uniform perturbations. Overall, these results suggest that formant variability is an important component of speech, and that our central nervous system takes into account such variability to produce more accurate speech output.
ContributorsDittman, Jonathan William (Author) / Daliri, Ayoub (Thesis director) / Berisha, Visar (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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The purpose of this study was to explore the relationship between acoustic indicators in speech and the presence of orofacial myofunctional disorder (OMD). This study analyzed the first and second formant frequencies (F1 and F2) of the four corner vowels [/i/, /u/, /æ/ and /ɑ/] found in the spontaneous

The purpose of this study was to explore the relationship between acoustic indicators in speech and the presence of orofacial myofunctional disorder (OMD). This study analyzed the first and second formant frequencies (F1 and F2) of the four corner vowels [/i/, /u/, /æ/ and /ɑ/] found in the spontaneous speech of thirty participants. It was predicted that speakers with orofacial myofunctional disorder would have a raised F1 and F2 because of habitual low and anterior tongue positioning. This study concluded no significant statistical differences in the formant frequencies. Further inspection of the total vowel space area of the OMD speakers suggested that OMD speakers had a smaller, more centralized vowel space. We concluded that more study of the total vowel space area for OMD speakers is warranted.
ContributorsWasson, Sarah Alicia (Co-author) / Wasson, Sarah (Co-author) / Weinhold, Juliet (Thesis director) / Daliri, Ayoub (Committee member) / College of Health Solutions (Contributor) / Hugh Downs School of Human Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique used in a variety of research settings, including speech neuroscience studies. However, one of the difficulties in using TMS for speech studies is the time that it takes to localize the lip motor cortex representation on the scalp. For my

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique used in a variety of research settings, including speech neuroscience studies. However, one of the difficulties in using TMS for speech studies is the time that it takes to localize the lip motor cortex representation on the scalp. For my project, I used MATLAB to create a software package that facilitates the localization of the ‘hotspot’ for TMS studies in a systematic, reliable manner. The software sends TMS pulses at certain locations, collects electromyography (EMG) data, and extracts motor-evoked potentials (MEPs) to help users visualize the resulting muscle activation. In this way, users can systematically find the subject’s hotspot for TMS stimulation of the motor cortex. The hotspot detection software was found to be an effective and efficient improvement on previous localization methods.

ContributorsKshatriya, Nyah (Author) / Daliri, Ayoub (Thesis director) / Liss, Julie (Committee member) / Barrett, The Honors College (Contributor) / Business (Minor) (Contributor)
Created2022-05