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A Design and Implementation of Youth Profanity Prevention Application Based on LLM and Generative AI

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2025, 30(3), pp.1~8
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : November 26, 2024
  • Accepted : January 13, 2025
  • Published : March 31, 2025

Ho-joon Kim 1 Hyun-dong Kim 2 Seo-hee Son 3 Sung-uk Bae 4 Ji-Won Ock 5 Sejong Lee 6

1서울과학기술대학교
2한국외국어대학교
3이화여자대학교
4건국대학교
5국방과학연구소
6영남대학교

Accredited

ABSTRACT

In this paper, we propose an AI-based service called Baleunmalssami aimed at fostering a positive language culture among adolescents and preventing cyberbullying. This service utilizes a classification model based on LLM and RAG to accurately detect offensive language and provide real-time suggestions for alternative expressions or emojis suited to the context, thus protecting the privacy of minors and reducing the use of profanity. The service consists of a keypad and an app. The keypad replaces offensive language with emojis that match the tone and provides a real-time risk rating for unethical expressions. The app uses accumulated text data analyzed by the LLM to automatically generate reports on language habits and cyberbullying for both students and parents. The KoSim-CSE-BERT-multitask model used in the keypad delivers fast and accurate results on-device without exposing data, while reports generated with LLM and RAG include only select portions of actual conversations to protect the privacy of minors. As a result, this service provides students with real-time language correction and self-awareness opportunities, while offering parents insightful information about their children’s language habits. Baleunmalssami will play an important role in fostering healthy language habits and contributing to a safer cyber environment.

Citation status

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