Performance Analysis of Personality Recognition on a Korean-Based Personality Recognition Dataset 


Vol. 14,  No. 8, pp. 643-649, Aug.  2025
https://doi.org/10.3745/TKIPS.2025.14.8.643


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  Abstract

As the demand for personalized services continues to grow, research on personality recognition using artificial intelligence (AI) based on the OCEAN model has been rapidly advancing. However, there is still a lack of Korean-language personality recognition datasets. To address this, the Korea Electronics Technology Institute (KETI) recruited participants and constructed a Korean-language personality recognition dataset. This study utilized the dataset to compare two experimental settings: one in which the data was split into training, validation, and test sets based on participant IDs, and another in which the video data was randomly split into these sets. Additionally, experiments were conducted using both full videos and videos containing only speech segments within each experimental setting. In the participant-based data partitioning experiments, the experiment using the full video of the third scenario (SCENE 3) achieved the best 1-MAE performance (0.9142). In contrast, in the random split experiments, the integrated experiment using the full video across all three scenarios achieved the highest 1-MAE performance (0.9931). These results suggest that data preprocessing and splitting methods significantly impact the performance of Korean-language personality recognition models. This study is meaningful in that it provides foundational insights for future multimodal fusion-based personality recognition research.

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[IEEE Style]

X. Qiu, M. Lee, J. Kim, B. Kim, "Performance Analysis of Personality Recognition on a Korean-Based Personality Recognition Dataset," The Transactions of the Korea Information Processing Society, vol. 14, no. 8, pp. 643-649, 2025. DOI: https://doi.org/10.3745/TKIPS.2025.14.8.643.

[ACM Style]

Xu Qiu, Mira Lee, Jeehyeong Kim, and Bongjae Kim. 2025. Performance Analysis of Personality Recognition on a Korean-Based Personality Recognition Dataset. The Transactions of the Korea Information Processing Society, 14, 8, (2025), 643-649. DOI: https://doi.org/10.3745/TKIPS.2025.14.8.643.

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