@article{ART003120960},
author={Seong-Gun Yun and Hyeok-Chan Kwon and Eunju Park and Youngbok Cho},
title={Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={9},
pages={79-87},
doi={10.9708/jksci.2024.29.09.079}
TY - JOUR
AU - Seong-Gun Yun
AU - Hyeok-Chan Kwon
AU - Eunju Park
AU - Youngbok Cho
TI - Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 9
PB - The Korean Society Of Computer And Information
SP - 79
EP - 87
SN - 1598-849X
AB - This study aims to improve communication for people with hearing impairments by developing artificial intelligence models that recognize and classify emotions from voice data. To achieve this, we utilized three major AI models: CNN-Transformer, HuBERT-Transformer, and Wav2Vec 2.0, to analyze users' voices in real-time and classify their emotions. To effectively extract features from voice data, we applied transformation techniques such as Mel-Frequency Cepstral Coefficient (MFCC), aiming to accurately capture the complex characteristics and subtle changes in emotions within the voice. Experimental results showed that the HuBERT-Transformer model demonstrated the highest accuracy, proving the effectiveness of combining pre-trained models and complex learning structures in the field of voice-based emotion recognition. This research presents the potential for advancements in emotion recognition technology using voice data and seeks new ways to improve communication and interaction for individuals with hearing impairments, marking its significance.
KW - Emotion Recognition;Transformer;HuBERT;Mel-Frequency Cepstral Coefficient
DO - 10.9708/jksci.2024.29.09.079
ER -
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park and Youngbok Cho. (2024). Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice. Journal of The Korea Society of Computer and Information, 29(9), 79-87.
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park and Youngbok Cho. 2024, "Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice", Journal of The Korea Society of Computer and Information, vol.29, no.9 pp.79-87. Available from: doi:10.9708/jksci.2024.29.09.079
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park, Youngbok Cho "Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice" Journal of The Korea Society of Computer and Information 29.9 pp.79-87 (2024) : 79.
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park, Youngbok Cho. Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice. 2024; 29(9), 79-87. Available from: doi:10.9708/jksci.2024.29.09.079
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park and Youngbok Cho. "Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice" Journal of The Korea Society of Computer and Information 29, no.9 (2024) : 79-87.doi: 10.9708/jksci.2024.29.09.079
Seong-Gun Yun; Hyeok-Chan Kwon; Eunju Park; Youngbok Cho. Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice. Journal of The Korea Society of Computer and Information, 29(9), 79-87. doi: 10.9708/jksci.2024.29.09.079
Seong-Gun Yun; Hyeok-Chan Kwon; Eunju Park; Youngbok Cho. Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice. Journal of The Korea Society of Computer and Information. 2024; 29(9) 79-87. doi: 10.9708/jksci.2024.29.09.079
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park, Youngbok Cho. Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice. 2024; 29(9), 79-87. Available from: doi:10.9708/jksci.2024.29.09.079
Seong-Gun Yun, Hyeok-Chan Kwon, Eunju Park and Youngbok Cho. "Design and Development of Open-Source-Based Artificial Intelligence for Emotion Extraction from Voice" Journal of The Korea Society of Computer and Information 29, no.9 (2024) : 79-87.doi: 10.9708/jksci.2024.29.09.079
