Machine Learning Applied to GRBAS Voice Quality Assessment
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 25743
- Type
- D - Journal article
- DOI
-
10.25046/aj030641
- Title of journal
- Advances in Science, Technology and Engineering Systems Journal
- Article number
- -
- First page
- 329
- Volume
- 3
- Issue
- 6
- ISSN
- 2415-6698
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
H - Computer Vision and Machine Learning Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Voice problems are routinely assessed in hospitals/clinics by speech and language therapists using 'GRBAS' voice-quality scoring. Our research uses machine learning for deriving these scores automatically. This paper results from collaboration with Salford Royal NHS Foundation Trust and Manchester University. It potentially allows voice problems to be assessed remotely using a smartphone and Internet technology, reducing the need for hospital appointments and increasing the efficiency of consultations. We are developing arrangements to evaluate this potential with our collaborators and there is some interest in the Computerised-GRBAS-Scoring-System from a commercial company, Key-Pentax Inc., that produces voice analysis equipment for hospitals world-wide.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
