Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages

ArXi:2503.18253v2 Announce Type: replace Developing and integrating emotion-understanding models are essential for a wide range of human-computer interaction tasks, including customer feedback analysis, marketing research, and social media monitoring. Given that users often express multiple emotions simultaneously within a single instance, annotating emotion datasets in a multi-label format is critical for capturing this complexity.