Abstract
Parkinson's disease (PD) is a central nervous system disorder that causes motor impairment. Recent studies have found that people with PD also often suffer from cognitive impairment (CI). While a large body of work has shown that speech can be used to predict motor symptom severity in people with PD, much less has focused on cognitive symptom severity. Existing work has investigated if acoustic features, derived from speech, can be used to detect CI in people with PD. However, these acoustic features are general and are not targeted toward capturing CI. Speech errors and disfluencies provide additional insight into CI. In this study, we focus on read speech, which offers a controlled template from which we can detect errors and disfluencies, and we analyze how errors and disfluencies vary with CI. The novelty of this work is an automated pipeline, including transcription and error and disfluency detection, capable of predicting CI in people with PD. This will enable efficient analyses of how cognition modulates speech for people with PD, leading to scalable speech assessments of CI.
Original language | English (US) |
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Title of host publication | 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 |
Publisher | International Speech Communication Association |
Pages | 156-160 |
Number of pages | 5 |
ISBN (Electronic) | 9781713836902 |
DOIs | |
State | Published - 2021 |
Event | 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 - Brno, Czech Republic Duration: Aug 30 2021 → Sep 3 2021 |
Publication series
Name | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
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Volume | 1 |
ISSN (Print) | 2308-457X |
ISSN (Electronic) | 1990-9772 |
Conference
Conference | 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 |
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Country/Territory | Czech Republic |
City | Brno |
Period | 8/30/21 → 9/3/21 |
Funding
This work was funded in part by Precision Health at University of Michigan. Funding for the data was provided by a National Institute of Deafness and Communication Disorders (NIDCD) grant to Dr. Angela Roberts (NIH/NIDCD 1R21DC017255-01). Data collection and analysis were approved by and conducted in accordance with current human subjects ethics guidelines at Northwestern University (PI: Dr. Angela Roberts). We thank the following people who were involved in the manual aspects of the annotations: Stephanie Gutierrez, Brenda Xu, Abi-gael Parrish, and Richard Richter. Data were made available for this project through a data use agreement executed between Dr. Angela Roberts (Northwestern University) and Dr. Emily Mower Provost (University of Michigan).
Keywords
- Cognitive impairment
- Disfluencies
- Parkinson's disease
- Read speech analysis
- Speech errors
ASJC Scopus subject areas
- Language and Linguistics
- Human-Computer Interaction
- Signal Processing
- Software
- Modeling and Simulation