SYSTEMATIC REVIEW article
Front. Artif. Intell.
Sec. Language and Computation
Volume 8 - 2025 | doi: 10.3389/frai.2025.1456245
Exploring the evolution and future prospects of Amharic to English machine translation: a systematic review
Provisionally accepted
- 1Adama Science and Technology University, Adama, Ethiopia
- 2University of Denver, Denver, Colorado, United States
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Amharic-English translation has undergone numerous improvements over the last few decades, beginning with rule-based systems and continuing with neural networks. The purpose of this systematic review is to examine the history, existing problems, and popular activities in the discipline, as well as the anticipated advancements in this field. Statistical machine translation accompanied the first attempts at neural machine translation with embedded transformers. Neural machine translation versions with transforms integrated into them provide higher accuracy and speed of translation. Amharic is still lacking in data, languages are poorly developed, and semantic and grammatical differences exist between the two languages. The construction of parallel text corpora, improved tokenization methods, and the use of neural machine translation models are becoming increasingly promising. Future directions will include improving data augmentation, refining token-level manipulation to preserve semantics, and integrating linguistic insights into parallel corpora to address Amharic's complex morphology. The development of comprehensive linguistic resources and standardized evaluation metrics is essential to advancing machine translation capabilities in Amharic and other under-resourced languages. Increasing technological inclusivity and cross-cultural communication requires accurate, context-aware translations.
Keywords: Machine Translation, Amharic, english, Systematic review, Low-resource languages
Received: 17 Oct 2024; Accepted: 29 Apr 2025.
Copyright: © 2025 Hussen Asebel, Getu Assefa and Abebe Haile. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Muluken Hussen Asebel, Adama Science and Technology University, Adama, Ethiopia
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