Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech: a Signal Processing Grand Challenge

Saturnino Luz, Fasih Haider, Davida Fromm, Ioulietta Lazarou, Ioannis Kompatsiaris +1 more
1/13/2023
eess.AScs.AIcs.CL

No official code found. Best implementation: AAISSJ/ADdetection (11 stars, MIT, last commit 2023-06-04).

Abstract

This Signal Processing Grand Challenge (SPGC) targets a difficult automatic prediction problem of societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD). Participants were invited to employ signal processing and machine learning methods to create predictive models based on spontaneous speech data. The Challenge has been designed to assess the extent to which predictive models built based on speech in one language (English) generalise to another language (Greek). To the best of our knowledge no work has investigated acoustic features of the speech signal in multilingual AD detection. Our baseline system used conventional machine learning algorithms with Active Data Representation of acoustic features, achieving accuracy of 73.91% on AD detection, and 4.95 root mean squared error on cognitive score prediction.

View on arXivView PDF

Code Implementations(1)

AAISSJ/ADdetectionCommunity71%
MIT

ICASSP 2023 SPGC Challenge: Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech

114PythonFeb 13, 20233 years agoMIT

Similar Papers

Benchmarking Foundation Speech and Language Models for Alzheimer's Disease and Related Dementia Detection from Spontaneous Speech

87% match2025

CAtCh: Cognitive Assessment through Cookie Thief

86% match1 repo12025

Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge

86% match2024

Linguistic Features Extracted by GPT-4 Improve Alzheimer's Disease Detection based on Spontaneous Speech

86% match1 repo22024

Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairment

86% match2025

Identification of Cognitive Decline from Spoken Language through Feature Selection and the Bag of Acoustic Words Model

86% match2024

Cite this paper

@article{luz2023multilingual,
  title  = {Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech: a Signal Processing Grand Challenge},
  author = {Saturnino Luz and Fasih Haider and Davida Fromm and Ioulietta Lazarou and Ioannis Kompatsiaris and Brian MacWhinney},
  year   = {2023},
  eprint = {2301.05562},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.05562v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2301.05562.svg)](https://codeofpaper.com/paper/2301.05562)

Discussion