Abstract
Children acquire language by interacting with their surroundings. Due to the different language environments each child is exposed to, the words they encounter and need in their life vary. Despite the standard tools for assessment and intervention as per predefined vocabulary sets, speech-language pathologists and parents struggle with the absence of systematic tools for child-specific custom vocabulary, i.e., out-of-standard but personally more important. We propose “Open Sesame? Open Salami! (OSOS)”, a personalized vocabulary assessment and intervention system with pervasive language profiling and targeted storybook generation, collaboratively developed with speech-language pathologists. Melded into a child's daily life and powered by large language models (LLM), OSOS profiles the child's language environment, extracts priority words therein, and generates bespoke storybooks naturally incorporating those words. We evaluated OSOS through 4-week-long deployments to 9 families. We report their experiences with OSOS, and its implications in supporting personalization outside standards.
Original language | English |
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Title of host publication | CHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Sytems |
Publisher | Association for Computing Machinery |
ISBN (Electronic) | 9798400703300 |
DOIs | |
State | Published - 11 May 2024 |
Event | 2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024 - Hybrid, Honolulu, United States Duration: 11 May 2024 → 16 May 2024 |
Publication series
Name | Conference on Human Factors in Computing Systems - Proceedings |
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Conference
Conference | 2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024 |
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Country/Territory | United States |
City | Hybrid, Honolulu |
Period | 11/05/24 → 16/05/24 |
Bibliographical note
Publisher Copyright:© 2024 Copyright held by the owner/author(s)
Keywords
- generative AI
- language assessment and intervention
- large language model
- storybook generation
- vocabulary learning