Research on self-training neural machine translation based on monolingual priority sampling
To enhance the performance of neural machine translation (NMT) and ameliorate the detrimental impact of high uncertainty in monolingual data during the self-training process, a self-training NMT model based on priority sampling was proposed. Initially, syntactic dependency trees were constructed and...
Saved in:
| Main Authors: | ZHANG Xiaoyan, PANG Lei, DU Xiaofeng, LU Tianbo, XIA Yamei |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2024-04-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2024066 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on self-training neural machine translation based on monolingual priority sampling
by: ZHANG Xiaoyan, et al.
Published: (2024-04-01) -
An Analysis of Syntactic Complexity in Texts Translated by Google Translate and Human Translator from Arabic into English
by: عزيز محمد عبده سعيد
Published: (2025-02-01) -
Analysis of Syntactic Errors in Translation From Russian to Kazakh Language
by: Bagdagul Mussa
Published: (2022-06-01) -
ACCURACY EVALUATION AND ERROR ANALYSIS OF DEPENDENCY PARSING FOR TEXTS IN UKRAINIAN
by: Костянтин Сироткін
Published: (2025-06-01) -
Lexico-Semantic and Structural Transformations of Biblical Text when Translated Into Ossetian Language
by: L. B. Morgoeva
Published: (2022-12-01)