Spoken dialogue systems are increasingly being used to facilitate and enhance human communication. While these interactive systems can process the linguistic aspects of human communication, they are not yet capable of processing the complex dynamics involved in social interaction, such as the adaptation on the part of interlocutors. Providing interactive systems with the capacity to process and exhibit this accommodation could however improve their efficiency and make machines more socially-competent interactants.At present, no automatic system is available to process prosodic accommodation, nor do any clear measures exist that quantify its dynamic manifestation. While it can be observed to be a monotonically manifest property, it is our hypotheses that it evolves dynamically with functional social aspects.In this paper, we propose an automatic system for its measurement and the capture of its dynamic manifestation. We investigate the evolution of prosodic accommodation in 41 Japanese dyadic telephone conversations and discuss its manifestation in relation to its functions in social interaction. Overall, our study shows that prosodic accommodation changes dynamically over the course of a conversation and across conversations, and that these dynamics inform about the naturalness of the conversation flow, the speakers' degree of involvement and their affinity in the conversation.

Objectives It is a concern that public health measures to prevent older people contracting COVID-19 could lead to a rise in mental health problems such as depression. The aim of this study therefore is to examinetrends of depressive symptomsbefore and during the COVID-19 pandemic in a large cohort of older people. Design Observational study with 6-year follow-up. Setting& Participants Over 3,000 community-dwelling adults aged ≥60 yearsparticipating in The Irish Longitudinal Study on Ageing (TILDA). Methods Mixed-effects multilevel models were used to describe trends in depressive symptoms across 3 waves of TILDA; Waves 4 (2016), 5 (2018) and a final wave conductedJuly-November 2020. Depressive symptoms were measured using 8-item CES-D, a score ≥9 indicating clinically significant symptoms. Results The prevalence of clinically significant depressive symptoms at Waves 4 and 5 was 7.2% (6.5–7.9) and 7.2% (6.5–8.0) respectively. This more than doubled to 19.8% (18.5–21.2) during the COVID-19 pandemic. There was no change in CES-D scores between Waves 4 and 5 (β=0.09 (-0.04 – 0.23) but a large increase in symptoms was observed during the pandemic (β=2.20 (2.07–2.33)). Age ≥70 years was independently associated with depressive symptoms (β=0.45 (0.18–0.72)) during the pandemic but notfrom Wave 4 to 5 (β=0.09 (-0.18–0.36)). Living with others was associated with lower burden of symptoms during the pandemic (β=-0.40 (-0.71 - -0.09)) but not between Waves 4 and 5 (β=-0.40 (-0.71 - -0.09)). Conclusions& Implications This study demonstrates significant increases in the burden of depressive symptoms amongst older people during the COVID-19 pandemic, particularly those aged ≥70 years and/or living alone. Even a small increase in the incidence of late life depression can have major implications for healthcare systems and societies in general. Improving access to age-attuned mental health care should therefore be a priority.

No abstract

Highlights Increased BMI, WHR, and waist size associated with lower cerebral blood flow. Waist size +1cm associated with same reduction in cerebral blood flow as +1year age. Higher levels of physical activity shown to potentially modify these associations.

Background: Speech and Language Impairments, generally attributed to lexico-semantic deficits, have been documented in Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). This study investigates the temporal organisation of speech (reflective of speech production planning) in reading aloud in relation to cognitive impairment, particularly working memory and attention deficits in MCI and AD. The discriminative ability of temporal features extracted from a newly designed read speech task is also evaluated for the detection of MCI and AD. Method: Sixteen patients with MCI, eighteen patients with mild-to-moderate AD and thirty-six healthy controls (HC) underwent a battery of neuropsychological tests and read a set of sentences varying in cognitive load, probed by manipulating sentence length and syntactic complexity. Results: Our results show that Mild-to-Moderate AD is associated with a general slowness of speech, attributed to a higher number of speech chunks, silent pauses and dysfluences, and slower speech and articulation rates. Speech chunking in the context of high cognitive-linguistic demand appears to be an informative marker of MCI, specifically related to early deficits in working memory and attention. In addition, Linear Discriminant Analysis shows the ROC AUCs (Areas Under the Receiver Operating Characteristic Curves) of identifying MCI vs. HC, MCI vs. AD and AD vs. HC using these speech characteristics are 0.75, 0.90 and 0.94 respectively. Conclusion: The implementation of connected speech-based technologies in clinical and community settings may provide additional information for the early detection of MCI and AD.