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In this study, the Bark transform and Lobanov method were used to normalize vowel formants in speech produced by persons with dysarthria. The computer classification accuracy of these normalized data were then compared to the results of human perceptual classification accuracy of the actual vowels. These results were then analyzed to determine if these techniques correlated with the human data.
Past studies have shown that auditory feedback plays an important role in maintaining the speech production system. Typically, speakers compensate for auditory feedback alterations when the alterations persist over time (auditory motor adaptation). Our study focused on how to increase the rate of adaptation by using different auditory feedback conditions. For the present study, we recruited a total of 30 participants. We examined auditory motor adaptation after participants completed three conditions: Normal speaking, noise-masked speaking, and silent reading. The normal condition was used as a control condition. In the noise-masked condition, noise was added to the auditory feedback to completely mask speech outputs. In the silent reading condition, participants were instructed to silently read target words in their heads, then read the words out loud. We found that the learning rate in the noise-masked condition was lower than that in the normal condition. In contrast, participants adapted at a faster rate after they experience the silent reading condition. Overall, this study demonstrated that adaptation rate can be modified through pre-exposing participants to different types auditory-motor manipulations.