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Breaking language barriers with ChatGPT: enhancing low-resource machine translation between algerian arabic and MSA

Published Online: 2024-05-23

Published Print: 2025-09

Authors

Babaali, Baligh https://orcid.org/0000-0001-7459-1964
Salem, Mohammed https://orcid.org/0000-0001-7052-5978
Alharbe, Nawaf R. https://orcid.org/0000-0002-1900-420X
License Information

Text and Data Mining valid from 2024-05-23

Version of Record valid from 2024-05-23
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Article History

Received: 21 January 2024

Accepted: 23 April 2024

First Online: 23 May 2024

Declarations

:

: We have no Conflict of interest to disclose. All authors declare that they have no Conflict of interest.

: Our objective is to conduct an experiment that investigates the efficacy of utilizing ChatGPT, a pre-trained language model, to enhance translation accuracy between two LRLs. For our research, we utilized publicly accessible datasets, and we have provided proper citations for their sources. It should be noted that publicly available datasets may contain biased sentences. Moreover, we have generated an in-house dataset for the MSA-DZDA language pair and have made the dataset accessible to other researchers by sharing the relevant link.

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