
Nabarun Halder
- Research Assistant, CCDS
Published at
UbiComp, IJCNN, HCII, IEEE Access
Research Interests
Machine Learning, Deep Learning, Natural Language Processing, Health Informatics, Human-Computer Interaction
Nabarun Halder, Armun Alam, Jahanggir Hossain Setu, Ashraful Islam, M. Ashraful Amin
2025 17th International Conference on Computer and Automation Engineering (ICCAE)
IEEE, pp. 6-11
Recognizing emotions from text is challenging, but transformers have greatly improved Natural Language Processing (NLP), making emotion detection more accurate. In this study, we performed a multi-class classification to recognize human emotion from Bangla text by developing an ensemble model combining the strengths of two models, BanglaBERT and MultiBERT, thereby enhancing the classification performance. We addressed the class imbalance in the dataset by applying back-translation to the minority classes, doubling their size. We evaluated the ensemble model on original and augmented datasets, comparing its performance with individual models. Results show that the ensemble approach significantly improves performance. Without data augmentation, the ensemble model achieves an accuracy of 0.68, with macro precision, recall, and F1-scores of 0.65, 0.59, and 0.61, respectively. After applying back-translation, accuracy improves to 0.74, with macro precision, recall, and F1-scores rising to 0.74. Especially, the “Anger” and “Disgust” classes showed significant F1-score improvements, rising from 0.48 to 0.70 and 0.39 to 0.66.

Published at
UbiComp, IJCNN, HCII, IEEE Access
Research Interests
Machine Learning, Deep Learning, Natural Language Processing, Health Informatics, Human-Computer Interaction

Published at
ECCV, Scientific Reports
Research Interests
Machine Learning

Assistant Professor
Department of Computer Science and Engineering
Independent University, Bangladesh (IUB)Published at
CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE
Research Interests
Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact

Professor
+1 more affiliationDepartment of Information Sciences and Technology
George Mason University, USA
Published at
ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE
Research Interests
Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics