Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challenge

• URL: http://arxiv.org/abs/2004.06833v3
• Date: Wed, 5 Aug 2020 22:44:29 GMT
• Title: Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challenge
• Authors: Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney
• Abstract summary: The ADReSS Challenge at INTERSPEECH 2020 defines a shared task through which different approaches to the automated recognition of Alzheimer's dementia 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.
• Score: 10.497861245133086
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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