In this paper, we introduce a dependency treebank of spoken second language (L2) English that is annotated with part of speech (Penn POS) tags and syntactic dependencies (Universal Dependencies). We then evaluate the degree to which the use of this treebank as training data affects POS and UD annotation accuracy for L1 web texts, L2 written texts, and L2 spoken texts as compared to models trained on L1 texts only.
|Title of host publication||BEA 2022 - 17th Workshop on Innovative Use of NLP for Building Educational Applications, Proceedings|
|Editors||Ekaterina Kochmar, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Nitin Madnani, Anais Tack, Victoria Yaneva, Zheng Yuan, Torsten Zesch|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||7|
|Publication status||Published - 2022|
|Event||17th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2022 - Seattle, United States|
Duration: 2022 Jul 15 → …
|Name||BEA 2022 - 17th Workshop on Innovative Use of NLP for Building Educational Applications, Proceedings|
|Conference||17th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2022|
|Period||22/7/15 → …|
Bibliographical noteFunding Information:
This project was supported by a Learning Early Career Research Grant.
© 2022 Association for Computational Linguistics.
All Science Journal Classification (ASJC) codes
- Language and Linguistics
- Linguistics and Language