A Korean emotion-factor dataset for extracting emotion and factors in Korean conversations.

ABSTRACT: Humans express their emotions in various ways, such as through facial expressions and voices. In particular, emotions are directly expressed or indirectly implied in the text of utterance. Research on the technology to identify emotions included in human speech and generate utterances is being conducted in conversational artificial intelligence technology. Despite the importance of recognizing the factors of previously generated emotions to generate emotion-based utterances, most of the existing datasets only provide the classification of emotions in text and utterances. In addition, in the case of Korean datasets, the classification of emotions is not diverse, and it is mainly biased toward negative emotion classification. In this paper, we propose KEmoFact, a Korean emotion-factor datase

SUBMITTER: Yoo S 

PROVIDER: S-EPMC10613607 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature