Semantic Babbling: Interactive Baby Robot System Using Large Language Models

摘要

Therapeutic robots are used in facilities for older people, but many of them can only provide mechanical responses to users. To improve the quality of interactions, it is crucial to address emotional consistency. Thus, we propose Semantic Babbling, a system that enables interaction with users by utilizing the baby robot's “inner voice”. By generating inner voices and selecting babbling based on sentiment, Semantic Babbling aims to mimic infant-like responses. A crowd-sourcing survey demonstrated the significance of emotional consistency and the display of inner voice in Semantic Babbling, revealing that it improves the impression of baby robots.