Research Output per year
Here is a brief summary of my research work.
Acoustic-based Assistive Technology Tool for Dysarthria Management
Clinical applications of speech processing technologies in the treatment and management of Dysarthria remains an underdeveloped research area over the years. This is owing to the fact that evidence-based intervention is challenging as this neurological speech disorder varies from one patient to another. There is, therefore, a need to identify acoustic features that are efficient in describing the characteristics targeted during a therapy session. There is also a need to investigate the relationship between acoustic modifications and what is perceived by human ear in an aim to increase speech intelligibility in dysarthria speakers.
Technology intervention in treatment and management of dysarthria will give both speech and language therapists and patients groups the opportunity to monitor the therapy progress over time. This research is aimed at developing an evidence for intervention, identification of relevant speech features in automatic severity classification and the design of a dysarthria management tool that can be used to track user’s progress. Speech features are extracted from dysarthric speech and used to identify cues that describe and distinguish this neurological disorder from other speech-related disorders.
Furthermore, a treatment tool, based on the evidence gathered, will be proposed in this research. The tool will assist patients, through case specific and tailor-made tasks, to improve their speech intelligibility, articulatory ability, ability to mark stress and voice quality. This will also avail the SLTs the ability to track patient’s progress quantitatively. Potential applications of these technologies will include treatment of other speech disorders, management of cognitive speech deficiencies, management of speech disorders in children and other advanced speech processing applications.
Master in Science, University Of Strathclyde
Sep 2013 → Sep 2014
Bachelor of Science in Engineering, University of Ibadan
Jun 2006 → Sep 2011
Graduate Training (Instrumentation Engineering), Nigeria LNG Ltd.6 Sep 2017 → …
Research output: Contribution to journal › Article
Automatic detection of speech disorder in dysarthria using extended speech feature extraction and neural networks classificationIjitona, T. B., Soraghan, J. J., Lowit, A., Di-Caterina, G. & Yue, H., 4 Dec 2017. 6 p.
Research output: Contribution to conference › Paper