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Masakhane Web: A Machine Translation Platform for African Languages

Domain:

natural language processing

Record type:

software
Creator:
CatSalAbiVukosi Marivate
Publisher:
Spr
Host:
Abstract Low-resource languages pose a particularly difficult challenge to neu-ral machine translation (NMT), and there appears to be insufficient machine translation (MT) systems to support African language accessibility. Masakhane Web, an NMT system for African languages, is proposed in this paper. Our approach is an open-source platform that is free, flexible, and produces reasonably accurate translations for African languages. The platform makes use of Masakhane community-trained MT models. It enables users to generate new data by providing feedback on translations, which is then used to retrain the models to improve them. Ultimately, our goal is to create a platform that can provide accurate translations for African languages and make the process of creating MT models easier for those who lack the technical expertise. Furthermore, we include strategies for domain experts to evaluate the system and explain how the platform can be used as a data collection source to improve MT for African languages.

Visit

doi.org

Tasks

machine translation

Licenses

https://creativecommons.org/licenses/by/4.0/

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Masakhane WEB - A Machine Translation Web Platform for African Languages

Adapted from https://github.com

Masakhane Web: A Machine Translation Platform for African Languages مسخاني ويب: منصة ترجمة آلية للغات الأفريقية Masakhane Web : une plateforme de traduction automatique pour les langues africaines Masakhane Web: una plataforma de traducción automática para idiomas africanos

Abstract Low-resource languages pose a particularly difficult challenge to neu-ral machine translati

Masakhane -- Machine Translation For Africa

Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is due to multiple factors, including: a lack of focus from government and funding, discov