Alhinti, L., Cunningham, S. orcid.org/0000-0001-9418-8726 and Christensen, H. orcid.org/0000-0003-3028-5062 (2020) Recognising emotions in dysarthric speech using typical speech data. In: Meng, H., Xu, B. and Zheng, T., (eds.) Interspeech 2020. Interspeech 2020, 25-29 Oct 2020, Shanghai, China. ISCA - International Speech Communication Association , pp. 4821-4825.
Abstract
Effective communication relies on the comprehension of both verbal and nonverbal information. People with dysarthria may lose their ability to produce intelligible and audible speech sounds which in time may affect their way of conveying emotions, that are mostly expressed using nonverbal signals. Recent research shows some promise on automatically recognising the verbal part of dysarthric speech. However, this is the first study that investigates the ability to automatically recognise the nonverbal part. A parallel database of dysarthric and typical emotional speech is collected, and approaches to discriminating between emotions using models trained on either dysarthric (speaker dependent, matched) or typical (speaker independent, unmatched) speech are investigated for four speakers with dysarthria caused by cerebral palsy and Parkinson’s disease. Promising results are achieved in both scenarios using SVM classifiers, opening new doors to improved, more expressive voice input communication aids.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Editors: |
|
Copyright, Publisher and Additional Information: | © 2020 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Dysarthria; emotion recognition; communication aids |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Jan 2021 09:43 |
Last Modified: | 14 Jan 2021 09:43 |
Published Version: | https://www.isca-speech.org/archive/Interspeech_20... |
Status: | Published |
Publisher: | ISCA - International Speech Communication Association |
Refereed: | Yes |
Identification Number: | 10.21437/interspeech.2020-1825 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:170038 |