ECRC: Emotion-Causality Recognition in Korean Conversation for GCN

arXiv:2403.10764v1 Announce Type: new
Abstract: In this multi-task learning study on simultaneous analysis of emotions and their underlying causes in conversational contexts, deep neural network methods were employed to effectively process and train large labeled datasets. However, these approaches are typically limited to conducting context analyses across the entire corpus because they rely on one of the two methods: word- or sentence-level embedding. The former struggles with polysemy and homonyms, whereas the latter causes information loss when processing long sentences. …

abstract analysis arxiv causality context conversation conversational cs.ai cs.cl datasets deep neural network emotion emotions however multi-task learning network neural network process recognition study train type