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A Parallel Corpora for bi-directional Neural Machine Translation for Low Resourced Ethiopian Languages

Type de record:

dataset
Créateur:
AtnMicMes
Éditeur:
IEEE
Hôte:

Visit

doi.org

Tasks

machine translation

Languages

Amharic

Licenses

https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.htmlhttps://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-037

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Parallel Corpora for bi-Directional Statistical Machine Translation for Seven Ethiopian Language Pairs

In this paper, we describe the development of parallel corpora for Ethiopian Languages: Amharic, Tigrigna, Afan-Oromo, Wolaytta and Geez. To check the usability of all the corpora we conducted baseline bi-directional statistical machine translation (SMT) experiment

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Improving neural machine translation for low resource languages through non-parallel corpora: a case study of Egyptian dialect to modern standard Arabic translation

Abstract Machine translation for low-resource languages poses significant challenges, primarily due