Low Resource Arabic Dialects Transformer Neural Machine Translation Improvement through Incremental Transfer of Shared Linguistic Features-Reference-Cited by-同舟云学术

Low Resource Arabic Dialects Transformer Neural Machine Translation Improvement through Incremental Transfer of Shared Linguistic Features

Published:2024-01-29 Issue:9 Volume:49 Page:12393-12409
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Slim Amel^ORCID,Melouah Ahlem

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13369-023-08543-9.pdf

Reference54 articles.

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3. Baniata, L.H.; Park, S.; Park, S.B.: A neural machine translation model for Arabic dialects that utilizes multitask learning (MTL). Comput. Intell. Neurosci. (2018). https://doi.org/10.1155/2018/7534712

4. Meftouh, K.; Harrat, S.; Jamoussi, S.; Abbas, M.; Smaili, K.: Machine Translation Experiments on PADIC: A Parallel Arabic Dialect Corpus. In: Proceedings of the 29th Pacific Asia Conference on Language Information and Computation, pp. 26–34 (2015)

5. Huang, P.; Zhao, J.; Sun, S.; Lin, Y.: Knowledge enhanced zero-resource machine translation using image-pivoting. Appl. Intell. 53(7), 7484–7496 (2023)

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