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- All Subjects: Speech Production
- All Subjects: speech science
- Creators: Daliri, Ayoub
- Creators: Perez Lustre, Sarahi
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
The brain continuously monitors speech output to detect potential errors between its sensory prediction and its sensory production (Daliri et al., 2020). When the brain encounters an error, it generates a corrective motor response, usually in the opposite direction, to reduce the effect of the error. Previous studies have shown that the type of auditory error received may impact a participant’s corrective response. In this study, we examined whether participants respond differently to categorical or non-categorical errors. We applied two types of perturbation in real-time by shifting the first formant (F1) and second formant (F2) at three different magnitudes. The vowel /ɛ/ was shifted toward the vowel /æ/ in the categorical perturbation condition. In the non-categorical perturbation condition, the vowel /ɛ/ was shifted to a sound outside of the vowel quadrilateral (increasing both F1 and F2). Our results showed that participants responded to the categorical perturbation while they did not respond to the non-categorical perturbation. Additionally, we found that in the categorical perturbation condition, as the magnitude of the perturbation increased, the magnitude of the response increased. Overall, our results suggest that the brain may respond differently to categorical and non-categorical errors, and the brain is highly attuned to errors in speech.
performance is limited by poor spectral resolution. Acoustic CI simulation has been widely used
in normal-hearing (NH) listeners to study the effect of spectral resolution on speech perception,
while avoiding patient-related confounds. It is unclear how speech production may change with
the degree of spectral degradation of auditory feedback as experience by CI users. In this study,
a real-time sinewave CI simulation was developed to provide NH subjects with auditory
feedback of different spectral resolution (1, 2, 4, and 8 channels). NH subjects were asked to
produce and identify vowels, as well as recognize sentences while listening to the real-time CI
simulation. The results showed that sentence recognition scores with the real-time CI simulation
improved with more channels, similar to those with the traditional off-line CI simulation.
Perception of a vowel continuum “HEAD”- “HAD” was near chance with 1, 2, and 4 channels,
and greatly improved with 8 channels and full spectrum. The spectral resolution of auditory
feedback did not significantly affect any acoustic feature of vowel production (e.g., vowel space
area, mean amplitude, mean and variability of fundamental and formant frequencies). There
was no correlation between vowel production and perception. The lack of effect of auditory
feedback spectral resolution on vowel production was likely due to the limited exposure of NH
subjects to CI simulation and the limited frequency ranges covered by the sinewave carriers of
CI simulation. Future studies should investigate the effects of various CI processing parameters
on speech production using a noise-band CI simulation.
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.