SingaKids: A Multilingual Multimodal Dialogic Tutor for Language Learning
Zhengyuan Liu, Geyu Lin, Hui Li Tan, Huayun Zhang, Yanfeng Lu, Xiaoxue Gao, Stella Xin Yin, He Sun, Hock Huan Goh, Lung Hsiang Wong, Nancy F. Chen

TL;DR
SingaKids is a multilingual, multimodal dialogic tutor that uses AI to facilitate language learning among young children across four languages, combining image captioning, speech understanding, and engaging interaction.
Contribution
The paper introduces SingaKids, a novel AI-powered multilingual dialogic tutor designed specifically for children, integrating multimodal features and scaffolding for effective language education.
Findings
Effective in engaging children across four languages
Improves language skills through interactive dialogue
Beneficial for learners at different levels
Abstract
The integration of generative artificial intelligence into educational applications has enhanced personalized and interactive learning experiences, and it shows strong potential to promote young learners language acquisition. However, it is still challenging to ensure consistent and robust performance across different languages and cultural contexts, and kids-friendly design requires simplified instructions, engaging interactions, and age-appropriate scaffolding to maintain motivation and optimize learning outcomes. In this work, we introduce SingaKids, a dialogic tutor designed to facilitate language learning through picture description tasks. Our system integrates dense image captioning, multilingual dialogic interaction, speech understanding, and engaging speech generation to create an immersive learning environment in four languages: English, Mandarin, Malay, and Tamil. We further…
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Taxonomy
TopicsInnovative Teaching and Learning Methods · Literacy and Educational Practices · EFL/ESL Teaching and Learning
