Abstract
In this paper, we discuss the results of the IUCL system in the NLI Shared Task 2017. For our system, we explore a variety of phonetic algorithms to generate features for Native Language Identification. These features are contrasted with one of the most successful type of features in NLI, character n-grams. We find that although phonetic features do not perform as well as character n-grams alone, they do increase overall F1 score when used together with character n-grams.- Anthology ID:
- W17-5046
- Volume:
- Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Joel Tetreault, Jill Burstein, Claudia Leacock, Helen Yannakoudakis
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 405–412
- Language:
- URL:
- https://aclanthology.org/W17-5046
- DOI:
- 10.18653/v1/W17-5046
- Cite (ACL):
- Charese Smiley and Sandra Kübler. 2017. Native Language Identification using Phonetic Algorithms. In Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pages 405–412, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Native Language Identification using Phonetic Algorithms (Smiley & Kübler, BEA 2017)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/W17-5046.pdf