What an "Ehm" Leaks About You: Mapping Fillers into Personality Traits with Quantum Evolutionary Feature Selection Algorithms
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22766800
- Type
- D - Journal article
- DOI
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10.1109/TAFFC.2019.2930695
- Title of journal
- IEEE Transactions on Affective Computing
- Article number
- 2930695
- First page
- -
- Volume
- 2020
- Issue
- -
- ISSN
- 2371-9850
- Open access status
- Not compliant
- Month of publication
- July
- Year of publication
- 2019
- URL
-
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- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first study proposing using fillers as an indicator of people's personalities, which provides a new direction for predicting human behaviour based on voice signals The work has inspired a continued collaboration with Prof Vinciarelli at the University of Glasgow to expand the research to new areas. In particular, new (as yet unpublished) research has been conducted at the University of Glasgow to diagnose depression and to analyse voice signals to diagnose COVID-19 patients via cough signals.
- Author contribution statement
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- Non-English
- No
- English abstract
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