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Bio-signal and Personality based Korean Emotion Recognition Challenge: KERC 2021
Eun-Chae Lim(임은채),Sudarshan Pant(판트 수다르산),Hyung-Jeong Yang(양형정),Guee-Sang Lee(이귀상),Soo-Hyung Kim(김수형) 한국컴퓨터교육학회 2022 한국컴퓨터교육학회 학술발표대회논문집 Vol.26 No.1
The 3rd Korean Emotion Recognition Challenge (KERC2021) focuses on Korean emotion recognition using a human bio-signal dataset annotated with emotions from 30 Koreans using the pre-selected video of Korean movies. The KERC2021 aims to develop a multimodal emotion recognition model to classify four quadrants of arousal and valence. In the challenge, 86 teams participated, and 7 teams were awarded the prize based on the ranking of classification F1-score. The participating teams performed classification using various machine learning models and deep neural networks to outperform the provided baseline classification model. This paper summarizes the dataset, baseline model, results of the challenge.