A Review of Automated Speech-Based Interaction for Cognitive Screening

Costas Boletsis

doi:10.3390/mti4040093

Abstract

Language, speech and conversational behaviours reflect cognitive changes that may precede physiological changes and offer a much more cost-effective option for detecting preclinical cognitive decline. Artificial intelligence and machine learning have been established as a means to facilitate automated speech-based cognitive screening through automated recording and analysis of linguistic, speech and conversational behaviours. In this work, a scoping literature review was performed to document and analyse current automated speech-based implementations for cognitive screening from the perspective of human–computer interaction. At this stage, the goal was to identify and analyse the characteristics that define the interaction between the automated speech-based screening systems and the users, potentially revealing interaction-related patterns and gaps. In total, 65 articles were identified as appropriate for inclusion, from which 15 articles satisfied the inclusion criteria. The literature review led to the documentation and further analysis of five interaction-related themes: (i) user interface, (ii) modalities, (iii) speech-based communication, (iv) screening content and (v) screener. Cognitive screening through speech-based interaction might benefit from two practices: (1) implementing more multimodal user interfaces that facilitate—amongst others—speech-based screening and (2) introducing the element of motivation in the speech-based screening process.

Highlights

Language impairment is common in prodromal dementia states such as mild cognitive impairment (MCI)
The literature review led to the documentation of five interaction-related themes, (i) user interface (UI), (ii) modalities, (iii) speech-based communication, (iv) screening content and (v) screener, all of which were further analysed in terms of their sub-categories and characteristics
The review showed that some automated speech-based systems for cognitive screening can screen exclusively for linguistic markers, featuring a voice user interface (VUI)

Summary

Introduction

Language impairment is common in prodromal dementia states such as mild cognitive impairment (MCI). Well-documented literature has identified the early disruption of normative patterns and processing of speech and language to be characteristic in patients with Alzheimer’s disease and in MCI stages [1,2]. Foundational clinical studies on language have highlighted changes in verbal fluency and naming [1,3]. Research has shown that MCI individuals with impairments in multiple domains, including language, are more likely to develop dementia compared to those with pure memory impairment [2]. Simple linguistic markers, such as word choice, verbal fluency, phrasing (i.e., ‘utterance’) and short speech patterns possess predictive power in assessing early cognitive decline status [1,4]. Speech and conversational behaviours reflect cognitive changes that may precede physiological changes and offer a much more cost-effective option for detecting preclinical cognitive decline [4,5]

Results

Discussion

Conclusion