Abstract
Code-mixed grapheme-to-phoneme (G2P) conversion is a crucial issue for modern speech recognition and synthesis task, but has been seldom investigated in sentence-level in literature. In this study, we construct a system that performs precise and efficient multi-stage code-mixed G2P conversion, for a less studied agglutinative language, Korean. The proposed system undertakes a sentence-level transliteration that is effective in the accurate processing of Korean text. We formulate the underlying philosophy that supports our approach and demonstrate how it fits with the contemporary document.- Anthology ID:
- 2020.calcs-1.9
- Volume:
- Proceedings of the The 4th Workshop on Computational Approaches to Code Switching
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Venue:
- CALCS
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 65–70
- Language:
- English
- URL:
- https://aclanthology.org/2020.calcs-1.9
- DOI:
- Cite (ACL):
- Won Ik Cho, Seok Min Kim, and Nam Soo Kim. 2020. Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration. In Proceedings of the The 4th Workshop on Computational Approaches to Code Switching, pages 65–70, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration (Cho et al., CALCS 2020)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2020.calcs-1.9.pdf