ArticleFrontiers in digital health2024
Understanding older people's voice interactions with smart voice assistants: a new modified rule-based natural language processing model with human input.
Article in Frontiers in digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Association Between Health Literacy and Outpatient Expenditure in Korea.Journal of Korean medical science · 2026Article
- Article
- Smart Speakers for Health and Well-Being of Older Adults: A Mixed-Methods Review.Healthcare (Basel, Switzerland) · 2025Review
- A Systematic Review of Natural Language Processing Techniques for Early Detection of Cognitive Impairment.Mayo Clinic proceedings. Digital health · 2025Review
- Multimodal fusion-powered English speaking robot.Frontiers in neurorobotics · 2024Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic has expedited the integration of Smart Voice Assistants (SVA) among older people. The qualitative data derived from user commands on SVA is pivotal for elucidating the engagement patterns of older individuals with such systems. However, the sheer volume of user-generated voice interaction data presents a formidable challenge for manual coding. Compounding this issue, age-related cognitive decline and alterations in speech patterns further complicate the interpretation of older users' SVA voice interactions. Conventional dictionary-based textual analysis tools, which count word frequencies, are inadequate in capturing the evolving and communicative essence of these interactions that unfold over a series of dialogues and modify with time. To address these challenges, our study introduces a novel, modified rule-based Natural Language Processing (MR-NLP) model augmented with human input. This reproducible approach capitalizes on human-derived insights to establish a lexicon of critical keywords and to formulate rules for the iterative refinement of the NLP model. English speakers, aged 50 or older and residing alone, were enlisted to engage with Amazon Alexa™ via predefined daily routines for a minimum of 30 min daily spanning three months (
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