Abstract: Clinical applications of speech technology face two challenges. The first is data sparsity. There is little data available to un- derpin techniques which are based on machine learning and, because it is difficult to collect disordered speech corpora, the only way to address this problem is by pooling what is produced from systems which are already in use. The second is person- alisation. This field demands individual solutions, technology which adapts to its user rather than demanding that the user adapt to it. Here we introduce a project, CloudCAST, which addresses these two problems by making remote, adaptive tech- nology available to professionals who work with speech: thera- pists, educators and clinicians.
Keywords: assistive technology, clinical applications of speech technology
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DOI:
10.17148/IJARCCE.2024.13666
