Characteristic Comparison of Korean Unstructured Dialogue Corpora by Morphological Analysis
Seona Moon, Saim Shin, San Kim, Minyoung Jung, Jin Yea Jang · 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS) · 2022
Natural language processing (NLP) has globally attracted researchers' attention. Many unstructured dialogue corpora in other languages as well as English and Chinese have been collected for NLP research. Those corpora show various characteristics depending on the relationship between speakers, the dialogue topic, how dialogues are gathered, etc. Analyzing their characteristics is therefore mandatory to comprehend the corpora for studying natural language dialogue. In this paper, we choose six different Korean unstructured dialogue corpora for their characteristic comparison, and identify the average numbers of utterances, proper nouns and pronouns per dialogue using MeCab-ko, a Korean morpheme analyzer.