A comparison of acoustic and linguistics methodologies for Alzheimer's dementia recognition

Nicholas Cummins, Yilin Pan, Zhao Ren, Julian Fritsch, Venkata Srikanth Nallanthighal, Heidi Christensen, Daniel Blackburn, Björn W. Schuller, Mathew Magimai-Doss, Helmer Strik, Aki Härmä

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

44 Scopus citations

Abstract

In the light of the current COVID-19 pandemic, the need for remote digital health assessment tools is greater than ever. This statement is especially pertinent for elderly and vulnerable populations. In this regard, the INTERSPEECH 2020 Alzheimer's Dementia Recognition through Spontaneous Speech (ADReSS) Challenge offers competitors the opportunity to develop speech and language-based systems for the task of Alzheimer's Dementia (AD) recognition. The challenge data consists of speech recordings and their transcripts, the work presented herein is an assessment of different contemporary approaches on these modalities. Specifically, we compared a hierarchical neural network with an attention mechanism trained on linguistic features with three acoustic-based systems: (i) Bag-of-Audio-Words (BoAW) quantising different low-level descriptors, (ii) a Siamese Network trained on log-Mel spectrograms, and (iii) a Convolutional Neural Network (CNN) end-to-end system trained on raw waveforms. Key results indicate the strength of the linguistic approach over the acoustics systems. Our strongest test-set result was achieved using a late fusion combination of BoAW, End-to-End CNN, and hierarchical-attention networks, which outperformed the challenge baseline in both the classification and regression tasks.

Original languageEnglish
Title of host publicationInterspeech 2020
PublisherInternational Speech Communication Association
Pages2182-2186
Number of pages5
ISBN (Print)9781713820697
DOIs
StatePublished - 2020
Externally publishedYes
Event21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020 - Shanghai, China
Duration: 25 Oct 202029 Oct 2020

Publication series

NameProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2020-October
ISSN (Print)2308-457X
ISSN (Electronic)1990-9772

Conference

Conference21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020
Country/TerritoryChina
CityShanghai
Period25/10/2029/10/20

Keywords

  • Alzheimer's Disease
  • Attention Mechanisms
  • Bag-of-Audio-Words
  • Convolutional Neural Network
  • Hierarchical Neural Network
  • Siamese Network

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