@article{ART003338900},
author={Jieun Lee and Young-Im Cho},
title={Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={5},
pages={123-132}
TY - JOUR
AU - Jieun Lee
AU - Young-Im Cho
TI - Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 5
PB - The Korean Society Of Computer And Information
SP - 123
EP - 132
SN - 1598-849X
AB - The need for sign language education to facilitate communication between the hearing-impaired and the general public is growing; however, limited access to professional institutions and the lack of real-time feedback hinder learning efficiency. This paper proposes a real-time Korean sign language recognition system that combines MediaPipe-based hand landmark extraction with an LSTM deep learning model. A dedicated dataset of 32 Korean sign language vocabularies was constructed under varied conditions, generating approximately 68,000 training sequences via a sliding window approach with an 80:20 train-test split. Experimental results demonstrate a recognition accuracy of 94.82% and a Marco F1-score of 0.95, with the LSTM model showing slightly higher accuracy and a more stable learning tendency compared to a GRU model. A cross-user evaluation achieved an average recognition rate of 83.3%, confirming practical generalization capability. The system is integrated with a web service to provide real-time feedback for improved accessibility in sign language education.
KW - Sign Language Recognition;Korean Sign Language;MediaPipe;LSTM;Deep Learning
DO -
UR -
ER -
Jieun Lee and Young-Im Cho. (2026). Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM. Journal of The Korea Society of Computer and Information, 31(5), 123-132.
Jieun Lee and Young-Im Cho. 2026, "Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM", Journal of The Korea Society of Computer and Information, vol.31, no.5 pp.123-132.
Jieun Lee, Young-Im Cho "Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM" Journal of The Korea Society of Computer and Information 31.5 pp.123-132 (2026) : 123.
Jieun Lee, Young-Im Cho. Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM. 2026; 31(5), 123-132.
Jieun Lee and Young-Im Cho. "Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM" Journal of The Korea Society of Computer and Information 31, no.5 (2026) : 123-132.
Jieun Lee; Young-Im Cho. Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM. Journal of The Korea Society of Computer and Information, 31(5), 123-132.
Jieun Lee; Young-Im Cho. Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM. Journal of The Korea Society of Computer and Information. 2026; 31(5) 123-132.
Jieun Lee, Young-Im Cho. Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM. 2026; 31(5), 123-132.
Jieun Lee and Young-Im Cho. "Real-Time Korean Sign Language Learning Recognition System Using MediaPipe and LSTM" Journal of The Korea Society of Computer and Information 31, no.5 (2026) : 123-132.
