| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-02-28 |
| タイトル |
|
|
タイトル |
Zero-shot cross-lingual transfer language selection using linguistic similarity |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源 |
http://purl.org/coar/resource_type/c_6501 |
|
タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
Juuso Eronen
Michal Ptaszynski
Fumito Masui
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
We study the selection of transfer languages for different Natural Language Processing tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In order to select an optimal transfer language, we propose to utilize different linguistic similarity metrics to measure the distance between languages and make the choice of transfer language based on this information instead of relying on intuition. We demonstrate that linguistic similarity correlates with cross-lingual transfer performance for all of the proposed tasks. We also show that there is a statistically significant difference in choosing the optimal language as the transfer source instead of English. This allows us to select a more suitable transfer language which can be used to better leverage knowledge from high-resource languages in order to improve the performance of language applications lacking data. For the study, we used datasets from eight different languages from three language families. |
|
言語 |
en |
| 書誌情報 |
en : Information Processing & Management
巻 60,
号 3,
発行日 2023-03
|
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
0306-4573 |
| DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1016/j.ipm.2022.103250 |
| 権利 |
|
|
言語 |
en |
|
権利情報 |
c2023 Elsevier Ltd. All rights reserved. |
| 出版者 |
|
|
出版者 |
Elsevier |
|
言語 |
en |
| 著者版フラグ |
|
|
言語 |
en |
|
値 |
author |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
2301.13720.pdf (29.1 MB)
