Variationist sociolinguistics has made significant contributions to linguistics and allied fields in the study of language variation and change. Yet within this paradigm, older adults remain understudied. There are non-trivial methodological challenges to collecting language data from the old age population. However, the Covid-19 pandemic led to increasing use of remote data collection methods that could fruitfully be employed with older adults. The MI Diaries project’s rich and growing collection of self-recorded ‘audio diaries’ via a custom mobile app demonstrates the success of this technology. An open-source version of the app, currently in development, will be adaptable to older users. For individuals who feel isolated, sending regular self-recordings to a responsive research team could be socially beneficial. As for variationist sociolinguistics, remote technologies could allow for greater engagement with outstanding research questions about older adults’ sociolinguistic identities and their participation in language change.
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Artificial Intelligence-Empowered Chatbot for Effective COVID-19 Information Delivery to Older Adults
The coronavirus disease 2019 (COVID-19) epidemic poses a threat to the everyday life of people worldwide and brings challenges to the global health system. During this outbreak, it is critical to find creative ways to extend the reach of informatics into every person in society. Although there are many websites and mobile applications for this purpose, they are insufficient in reaching vulnerable populations like older adults who are not familiar with using new technologies to access information. In this paper, we propose an AI-enabled chatbot assistant that delivers real-time, useful, context-aware, and personalized information about COVID-19 to users, especially older adults. To use the assistant, a user simply speaks to it through a mobile phone or a smart speaker. This natural and interactive interface does not require the user to have any technical background. The virtual assistant was evaluated in the lab environment through various types of use cases. Preliminary qualitative test results demonstrate a reasonable precision and recall rate.
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- Award ID(s):
- 1722913
- PAR ID:
- 10312990
- Date Published:
- Journal Name:
- International Journal of E-Health and Medical Communications
- Volume:
- 12
- Issue:
- 6
- ISSN:
- 1947-315X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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