Abstract
In Korean, quantitative speech act studies have usually been conducted on single utterances with unspecified sources. In this study, we annotate sentences from the National Institute of Korean Language’s Messenger Corpus and the National Petition Corpus, as well as example sentences from an academic paper on contemporary Korean vlogging, and check the discrepancy between human annotation and model prediction. In particular, for sentences with differences in locutionary and illocutionary forces, we analyze the causes of errors to see if stylistic features used in a particular domain affect the correct inference of speech act. Through this, we see the necessity to build and analyze a balanced corpus in various text domains, taking into account cases with different usage roles, e.g., messenger conversations belonging to private conversations and petition corpus/vlogging script that have an unspecified audience.- Anthology ID:
- 2023.nlp4dh-1.26
- Volume:
- Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages
- Month:
- December
- Year:
- 2023
- Address:
- Tokyo, Japan
- Editors:
- Mika Hämäläinen, Emily Öhman, Flammie Pirinen, Khalid Alnajjar, So Miyagawa, Yuri Bizzoni, Niko Partanen, Jack Rueter
- Venues:
- NLP4DH | IWCLUL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 229–234
- Language:
- URL:
- https://aclanthology.org/2023.nlp4dh-1.26
- DOI:
- Cite (ACL):
- Youngsook Song and Won Ik Cho. 2023. Study on the Domain Adaption of Korean Speech Act using Daily Conversation Dataset and Petition Corpus. In Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages, pages 229–234, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- Study on the Domain Adaption of Korean Speech Act using Daily Conversation Dataset and Petition Corpus (Song & Cho, NLP4DH-IWCLUL 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.nlp4dh-1.26.pdf