Mirheidari, B., Blackburn, D., Reuber, M. et al. (2 more authors) (2016) Diagnosing people with dementia using automatic conversation analysis. In: Proceedings of Interspeech. Interspeech, 08-12 Sep 2016, San Francisco, CA. ISCA , pp. 1220-1224.
Abstract
A recent study using Conversation Analysis (CA) has demonstrated that communication problems may be picked up during conversations between patients and neurologists, and that this can be used to differentiate between patients with (progressive neurodegenerative dementia) ND and those with (nonprogressive) functional memory disorders (FMD). This paper presents a novel automatic method for transcribing such conversations and extracting CA-style features. A range of acoustic, syntactic, semantic and visual features were automatically extracted and used to train a set of classifiers. In a proof-of-principle style study, using data recording during real neurologist-patient consultations, we demonstrate that automatically extracting CA-style features gives a classification accuracy of 95%when using verbatim transcripts. Replacing those transcripts with automatic speech recognition transcripts, we obtain a classification accuracy of 79% which improves to 90% when feature selection is applied. This is a first and encouraging step towards replacing inaccurate, potentially stressful cognitive tests with a test based on monitoring conversation capabilities that could be conducted in e.g. the privacy of the patient’s own home.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 ISCA. This is an author produced version of a paper subsequently published in Interspeech. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number ALZHEIMERS RESEARCH UK ARUK-PPG2014B-25 NATIONAL INSTITUTE FOR HEALTH RESEARCH UNSPECIFIED |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Nov 2016 10:59 |
Last Modified: | 19 Dec 2022 13:34 |
Published Version: | http://dx.doi.org/10.21437/Interspeech.2016-857 |
Status: | Published |
Publisher: | ISCA |
Refereed: | Yes |
Identification Number: | 10.21437/Interspeech.2016-857 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:106798 |