Honorable Mention
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.
doi.org/10.1145/3613904.3642580
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)