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Automated screening for Alzheimer's dementia through spontaneous speech

conference contribution
posted on 2024-11-03, 13:56 authored by Muhammad Shehram Shah Syed, Zafi Syed, Margaret LechMargaret Lech, Elena PirogovaElena Pirogova
Dementia is a neurodegenerative disease that leads to cognitive and (eventually) physical impairments. Individuals who are affected by dementia experience deterioration in their capacity to perform day-to-day tasks thereby significantly affecting their quality of life. This paper addresses the Interspeech 2020 Alzheimer's' Dementia Recognition through Spontaneous Speech (ADReSS) challenge where the objective is to propose methods for two tasks. The first task is to identify speech recordings from individuals with dementia amongst a set of recordings which also include those from healthy individuals. The second task requires participants to estimate the Mini-Mental State Examination (MMSE) score based on an individual's speech alone. To this end, we investigated characteristics of speech paralinguistics such as prosody, voice quality, and spectra as well as VGGish based deep acoustic embedding for automated screening for dementia based on the audio modality. In addition to this, we also computed deep text embeddings for transcripts of speech. For the classification task, our method achieves an accuracy of 85.42% compared to the baseline of 62.50% on the test partition, meanwhile, for the regression task, our method achieves an RMSE = 4.30 compared to the baseline of 6.14. These results show the promise of our proposed methods for the task of automated screening for dementia based on speech alone. Copyright

History

Volume

2020-October

Start page

2222

End page

2226

Total pages

5

Outlet

Proceedings of the 21st Annual Conference of the International Speech Communication Association (INTERSPEECH 2020)

Name of conference

INTERSPEECH 2020: Cognitive Intelligence for Speech Processing

Publisher

International Speech Communication Association

Place published

Baixas, France

Start date

2020-10-25

End date

2020-10-29

Language

English

Copyright

Copyright © 2020 ISCA

Former Identifier

2006106341

Esploro creation date

2021-06-01

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