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Smartphone: Exploring Keyword Mnemonic With Auto-Generated Verbal And Visual Cues

Conference Paper/Proceedings
Smartphone: Exploring Keyword Mnemonic With Auto-Generated Verbal And Visual Cues
Publication Year:
2023
Publication Source:
Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics)
Volume:
13916 LNAI
Funding Type:
ECR:Core
Author(s):
Lee, Jaewook; Lan, Andrew
Supporting Project(s):

In second language vocabulary learning, existing works have primarily focused on either the learning interface or scheduling personalized retrieval practices to maximize memory retention. However, the learning content, i.e., the information presented on flashcards, has mostly remained constant. Keyword mnemonic is a notable learning strategy that relates new vocabulary to existing knowledge by building an acoustic and imagery link using a keyword that sounds alike. Beyond that, producing verbal and visual cues associated with the keyword to facilitate building these links requires a manual process and is not scalable. In this paper, we explore an opportunity to use large language models to automatically generate verbal and visual cues for keyword mnemonics. Our approach, an end-to-end pipeline for auto-generating verbal and visual cues, can automatically generate highly memorable cues. We investigate the effectiveness of our approach via a human participant experiment by comparing it with manually generated cues. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.