ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events

Fuente: arXiv
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Main Authors: Seo, Woosuk, Yang, Chanmo, Kim, Young-Ho
Format: Preprint
Published: 2023
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author Seo, Woosuk
Yang, Chanmo
Kim, Young-Ho
author_facet Seo, Woosuk
Yang, Chanmo
Kim, Young-Ho
contents Children typically learn to identify and express emotions through sharing their stories and feelings with others, particularly their family. However, it is challenging for parents or siblings to have emotional communication with children since children are still developing their communication skills. We present ChaCha, a chatbot that encourages and guides children to share personal events and associated emotions. ChaCha combines a state machine and large language models (LLMs) to keep the dialogue on track while carrying on free-form conversations. Through an exploratory study with 20 children (aged 8-12), we examine how ChaCha prompts children to share personal events and guides them to describe associated emotions. Participants perceived ChaCha as a close friend and shared their stories on various topics, such as family trips and personal achievements. Based on the findings, we discuss opportunities for leveraging LLMs to design child-friendly chatbots to support children in sharing emotions.
format Preprint
id arxiv_https___arxiv_org_abs_2309_12244
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
Seo, Woosuk
Yang, Chanmo
Kim, Young-Ho
Human-Computer Interaction
Artificial Intelligence
Computation and Language
H.5.2; I.2.7
Children typically learn to identify and express emotions through sharing their stories and feelings with others, particularly their family. However, it is challenging for parents or siblings to have emotional communication with children since children are still developing their communication skills. We present ChaCha, a chatbot that encourages and guides children to share personal events and associated emotions. ChaCha combines a state machine and large language models (LLMs) to keep the dialogue on track while carrying on free-form conversations. Through an exploratory study with 20 children (aged 8-12), we examine how ChaCha prompts children to share personal events and guides them to describe associated emotions. Participants perceived ChaCha as a close friend and shared their stories on various topics, such as family trips and personal achievements. Based on the findings, we discuss opportunities for leveraging LLMs to design child-friendly chatbots to support children in sharing emotions.
title ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
topic Human-Computer Interaction
Artificial Intelligence
Computation and Language
H.5.2; I.2.7
url https://arxiv.org/abs/2309.12244