Communication disorders affect one in ten Canadians and the incidence is particularly high among those with Cerebral Palsy. A vocalization-activated switch is often explored as an alternative means to communication. However, most commercial speech recognition tools to date have limited capability to accommodate dysarthric speech and thus are often prematurely abandoned. We developed and evaluated a novel vocalization-based access technology as a writing tool for a pediatric participant with cerebral palsy. It consists of a high quality condenser headmic, a custom classifier based on Gaussian Mixture Modeling (GMM) and Mel-frequency Cepstral Coefficients (MFCC) as features. The system was designed to discriminate among five vowel sounds while interfaced to an on-screen keyboard. We used response efficiency theory to assess this technology in terms of goal attainment and satisfaction. The participant’s primary goal to reduce switch activation time was achieved with increased satisfaction and lower physical effort when compared to her previous pathway.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/42954 |
| Date | 28 November 2013 |
| Creators | Thalanki Anantha, Nayanashri |
| Contributors | Chau, Tom |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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