Home
Atlas
Insights
Docs
Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Towards Guided Back-translation for Low-resource languages- A Case Study on Kabyle-French

Record type:

paper

Creator:

NasFatNas

Publisher:

IEEE

Host:

Visit

Tasks

machine translation

Languages

Licenses

https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037

Similar

Data Augmentation With Back translation for Low Resource languages: A case of English and LugandaNeural Machine Translation for Extremely Low-Resource African Languages: A Case Study on BambaraSynthetic Data Diversity vs. Back-Translation for Multilingual NER in Low-Resource LanguagesEmbedding Initialization for Unseen Low-resource Languages in Multilingual NMT: A Case Study on Limbum-English TranslationKabyle/French Codeswitching: a case studyContributing to Speech-to-Speech Translation for African Low-Resource Languages : Study of French-Mooré Pair

Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda

In this paper,we explore the application of Back translation (BT) as a semi-supervised technique to

Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara

Low-resource languages present unique challenges to (neural) machine translation. We discuss the cas

Synthetic Data Diversity vs. Back-Translation for Multilingual NER in Low-Resource Languages

Named Entity Recognition(NER) for low-resource languages aims to produce robust systems for language

Embedding Initialization for Unseen Low-resource Languages in Multilingual NMT: A Case Study on Limbum-English Translation

Multilingual neural machine translation models such as NLLB-200 cover 200 languages but leave thousa

Kabyle/French Codeswitching: a case study

Contributing to Speech-to-Speech Translation for African Low-Resource Languages : Study of French-Mooré Pair