Machine Translation Performance for Low-Resource Languages: A Systematic Literature Review
Machine translation (MT) for low-resource languages continues to face significant challenges because of limited digital resources and parallel corpora, despite remarkable developments in neural machine translation (NMT). Addressing these challenges requires a thorough review of existing research to...
Saved in:
| Main Authors: | Taofik O. Tafa, Siti Zaiton Mohd Hashim, Mohd Shahizan Othman, Hitham Alhussian, Maged Nasser, Said Jadid Abdulkadir, Sharin Hazlin Huspi, Sarafa O. Adeyemo, Yunusa Adamu Bena |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10972018/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Translation Quality Regarding Low-Resource, Custom Machine Translations: A Fine-Grained Comparative Study on Turkish-to-English Statistical and Neural Machine Translation Systems
by: Gökhan Doğru
Published: (2022-12-01) -
Perspektywy rozwoju tłumaczenia maszynowego (na przykładzie angielsko-rosyjskich relacji przekładowych)
by: Jakub Olas
Published: (2019-09-01) -
The Machine Translation (MT) of Proverbs in the ENG-PL Language Pair
by: Romaniuk-Cholewska Dominika
Published: (2024-12-01) -
Machine Translation Evaluation between Arabic and English during 2020 to 2024: A Review Study
by: Aziz Mohammed Abdo Saeed
Published: (2025-05-01) -
Web-Based Google Translate Inconsistencies in Bahasa-Arabic Translations from the Arabic Thesis Writer's Perspective
by: Rahmat Satria Dinata, et al.
Published: (2024-03-01)