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

Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 a feature extraction procedure and results for a classification and a regression model. ADReSS aims to provide the speech and language Alzheimer's research community with a platform for comprehensive methodological comparisons. This will contribute to addressing the lack of standardisation that currently affects the field and shed light on avenues for future research and clinical applicability.
Original languageEnglish
Title of host publicationINTERSPEECH 2020
PublisherISCA
Pages2172-2176
Number of pages5
DOIs
Publication statusPublished - 16 Oct 2020
EventInterspeech 2020 - Virtual Conference, China
Duration: 25 Oct 202029 Oct 2020
http://www.interspeech2020.org/

Conference

ConferenceInterspeech 2020
Abbreviated titleINTERSPEECH 2020
CountryChina
CityVirtual Conference
Period25/10/2029/10/20
Internet address

Keywords

  • eess.AS
  • cs.LG
  • stat.ML

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