A computational linguistic analysis of speech in elderly individuals with cognitive decline: the “Anchise-2022”

Francesco Sigona; Barbara Gili Fivela; Pietro Vigorelli; Andrea Bolioli

doi:10.17469/O2111AISV000012

Authors

Francesco Sigona Laboratory CRIL (Centro di Ricerca Interdisciplinare sul Linguaggio) & DReaM, Department of Humanities, University of Salento, Lecce, Italy https://orcid.org/0000-0003-2939-0009
Barbara Gili Fivela Laboratory CRIL & DReaM, Department of Humanities, University of Salento, Lecce, Italy https://orcid.org/0000-0002-4694-8652
Pietro Vigorelli Gruppo Anchise, Milan, Italy
Andrea Bolioli Independent researcher, Turin, Italy

DOI:

https://doi.org/10.17469/O2111AISV000012

Keywords:

MMSE, NLP, Linguistic features, Ecological conversations, Enabling Approach

Abstract

In this article, we introduce the “Anchise-2022” corpus, the latest update of the “Anchise” corpus, with approximately 600 manually transcribed conversations, mainly between healthcare providers and elderly individuals with cognitive decline (dementia, Alzheimer's disease). We also analysed over 200 of these transcripts, to check if and to what extent we can correlate characteristics of such kind of speech production with the progression of dementia as measured by Mini-Mental State Examination (MMSE). To this purpose, we adopted computational linguistic analysis using Natural Language Processing (NLP) techniques, statistical-descriptive and inferential analysis. The results obtained allow us to assert, in line with existing literature, that certain parameters exhibit a degree of correlation with MMSE values. Additionally, it is feasible to utilize automatic classification techniques to infer the degree of linguistic/cognitive impairment.