Alzheimer’s Dementia Recognition Through Spontaneous Speech: The ADReSS Challenge
Open accessAbstract
The ADReSS Challenge at INTERSPEECH 2020 defines a shared task through which different approaches to the automated recognition of Alzheimer's dementia based on spontaneous speech can be compared. ADReSS provides researchers with a benchmark speech dataset which has been acoustically pre-processed and balanced in terms of age and gender, defining two cognitive assessment tasks, namely: the Alzheimer's speech classification task and the neuropsychological score regression task. In the Alzheimer's speech classification task, ADReSS challenge participants create models for classifying speech as dementia or healthy control speech. In the the neuropsychological score regression task, participants create models to predict mini-mental state examination scores. This paper describes the ADReSS Challenge in detail and presents a baseline for both tasks, including feature extraction procedures and results for classification and regression models. ADReSS aims to provide the speech and language Alzheimer's research community with a platform for comprehensive methodological comparisons. This will hopefully contribute to addressing the lack of standardisation that currently affects the field and shed light on avenues for future research and clinical applicability.
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Dementia Speech Dataset Creation and Analysis in Indic Languages—A Pilot Study
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Useful blunders: Can automated speech recognition errors improve downstream dementia classification?
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Paralinguistic and linguistic fluency features for Alzheimer's disease detection
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Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls
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Self-citation
- Authors
- Luz, S., Haider, F., Fuente, S. D. L., Fromm, D., & MacWhinney, B.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- Interspeech 2020
- Publisher
- ISCA
- Published
- 2020-10-25
- Pages
- 2172-2176
- ISSN
- 2308-457X (ISSN-L)
- OpenAlex
- W3016396388
- Cited by
- 274
- References
- 19
- Citations by year
- 2026: 29 · 2025: 45 · 2024: 46 · 2023: 45 · 2022: 41 · 2021: 42 · 2020: 26
- FWCI
- 60.28
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Interspeech (USB) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- European Commission (HORIZON2020, 769661)
- Medical Research Council
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- Alzheimer's disease, dementia detection, spontaneous speech, speech classification, Mini-Mental State Examination, benchmark dataset, shared task, cognitive assessment
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