Effects of Age-Related Cognitive Decline on Elderly User Interactions with Voice-Based Dialogue Systems
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Speech disfluency can represent an accessibility barrier to voice assistants.
“As reported in a previous study, speech disfluency can represent an accessibility barrier to voice assistants.”
From Investigating the Accessibility of Voice Assistants With Impaired Users: Mixed Methods Study (2020) · cites this paper as [23]
The Abstract reports that pauses and hesitations in older adults’ speech were associated with cognitive scores during voice-system interactions. It also mentions differences in handling recognition errors, but does not establish that speech disfluency itself caused those errors or posed an accessibility barrier. (LLM, conf=0.76)
Experimental — accuracy not yet measuredPrior research has proposed design guidelines to tailor voice-based interfaces for effective use by older adults with cognitive decline.
“Hence, prior research has proposed design guidelines to tailor voice-based interfaces for effective use by older adults with cognitive decline [104].”
From Conversational Affective Social Robots for Ageing and Dementia Support (2022) · cites this paper as [104]
Long hesitations or pauses can be misinterpreted by the system as a sentence delimiter, causing an alteration of speech segmentation.
“For instance, long hesitations or pauses can be misinterpreted by the system as a sentence delimiter [23], causing an alteration of speech segmentation.”
From Investigating the Accessibility of Voice Assistants With Impaired Users: Mixed Methods Study (2020) · cites this paper as [23]
The Abstract reports pauses and hesitations as vocal characteristics related to cognitive scores, but does not say that the system treats long pauses as sentence delimiters or changes speech segmentation. Searches for “sentence delimiter” and for pauses with speech recognition and segmentation found no passage addressing that mechanism in our copy. (LLM, conf=0.72)
Experimental — accuracy not yet measured
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“For instance, long hesitations or pauses can be misinterpreted by the system as a sentence delimiter [23], causing an alteration of speech segmentation.”
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Exploring the Use of Voice Assistants in Nursing Homes
Cerezo, E., Lacuesta, R., Gallardo, J., & Aguelo, A. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2470282 · Cited by 4 · see citing works
Yuan, F., Zhang, R., Bilal, D., & Zhao, X. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90525-5_37 · Cited by 4 · see citing works
Yamada, Y., Shinkawa, K., Kosugi, A., Kobayashi, M., Takagi, H., Nemoto, M., Nemoto, K., & Arai, T. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-51057-2_19 · Cited by 4 · see citing works
Self-citationPerancangan Desain Antarmuka Buku Kontak Untuk Lansia
Sebastián, D., Hermawan, H., Restyandito, R., & Nugraha, K. A. (2022) · AITI · doi:10.24246/aiti.v19i2.167-184 · Cited by 3 · see citing works
Mahmood, A., Wang, J., & Huang, C.-M. (2026) · ACM Transactions on Accessible Computing · doi:10.1145/3796236 · Cited by 6 · see citing works
“Moreover, we observed cases where LLMs absorbed imperfect inputs and still advanced the task ( e.g., C6’s truncated utterance due to VA interruption), consistent with prior findings that LLMs can mitigate recognition issues or trigger recovery prompts [48].”
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Digital Measures of Drawing Process to Predict Multiple Cognitive and Gait Measures in Older Adults
Yamada, Y., Kobayashi, M., Shinakwa, K., Nemoto, M., Ota, M., Nemoto, K., & Arai, T. (2024) · IEEE International Conference on Digital Health (ICDH) · doi:10.1109/icdh62654.2024.00042 · Cited by 2 · see citing works
Self-citationValidation of DigiMoCA, A Conversational Agent for the Cognitive Assessment of Senior Adults
Pacheco-Lorenzo, M. R., Valladares‐Rodríguez, S., Iglesias, M. J. F., & Anido, L. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2537783 · Cited by 1 · see citing works
Pacheco-Lorenzo, M. R., Valladares‐Rodríguez, S., Anido, L., & Iglesias, M. J. F. (2022) · Algorithms for intelligent systems · doi:10.1007/978-981-16-6332-1_65 · Cited by 1 · see citing works
Conversational Analysis Agents for Depression Detection: A Systematic Review
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Older Adults’ Voice Search through the Human-Engaged Computing Perspective
Yuan, X., & Ren, X. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-90176-9_39
A systematic review of the relationships amongst older adults’ cognitive and motor speech abilitiesPreprint
Manderson, L., Krzeczkowska, A., Kuschmann, A., Lowit, A., & Brown, L. A. (2022) · doi:10.31234/osf.io/xmz2p
(2022) · transcript Verlag eBooks · doi:10.1515/9783839459249
Krämer, D., Haltaufderheide, J., & Vollmann, J. (2022) · Digitale Gesellschaft · doi:10.14361/9783839459249
Zou, Q. C., & Wu, L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29839-3_16
- Authors
- Kobayashi, M., Kosugi, A., Takagi, H., Nemoto, M., Nemoto, K., Arai, T., & Yamada, Y.
- Affiliations
- IBM Research - Tokyo (JP)
- University of Tsukuba (JP)
- Corresponding author
- Kobayashi, Masatomo
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Volume
- LNCS-11749
- Issue
- Part IV
- Pages
- 53-74
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2970679586
- Cited by
- 45
- References
- 66
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 4 · 2023: 7 · 2022: 12 · 2021: 10 · 2020: 3
- FWCI
- 21.31
- Type
- conference paper
- Language
- en
- Open access
- green
- inria.hal.science
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- HAL (submittedVersion, cc-by)
- Funders
- Japan Society for the Promotion of Science (19H01084)
- Topics
- Social Sciences › Demography › Technology Use by Older Adults
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- age-related cognitive decline, older adults, smart speakers, voice assistants, user interaction, error handling, intent classification, user experience
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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