Abstract
In this paper, we discuss the development of a part-of-speech tagger for English-Assamese code-mixed texts. We provide a comparison of 2 approaches to annotating code-mixed data – a) annotation of the texts from the two languages using monolingual resources from each language and b) annotation of the text through a different resource created specifically for code-mixed data. We present a comparative study of the efforts required in each approach and the final performance of the system. Based on this, we argue that it might be a better approach to develop new technologies using code-mixed data instead of monolingual, ‘clean’ data, especially for those languages where we do not have significant tools and technologies available till now.- Anthology ID:
- W18-4110
- Volume:
- Proceedings of the First International Workshop on Language Cognition and Computational Models
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Manjira Sinha, Tirthankar Dasgupta
- Venue:
- LCCM
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 94–103
- Language:
- URL:
- https://aclanthology.org/W18-4110
- DOI:
- Cite (ACL):
- Ritesh Kumar and Manas Jyoti Bora. 2018. Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches. In Proceedings of the First International Workshop on Language Cognition and Computational Models, pages 94–103, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches (Kumar & Bora, LCCM 2018)
- PDF:
- https://preview.aclanthology.org/fix-volume-bibkeys/W18-4110.pdf