Low-resource Machine Translation recently gained a lot of popularity, and for certain languages, it
Millions of people around the world can not access content on the Web because most of the content is not readily available in their language. Machine translation (MT) systems have the potential to change this for many languages. Current MT systems provide very accu
Human evaluation dataset to evaluate machine translation systems to and from Amharic, English and Tigrinya.
We conduct an empirical study of neural machine translation (NMT) for truly low-resource languages,
The quality of a Neural Machine Translation system depends substantially on the availability of siza
Pivot pre-finetuning for low-resource machine translation Poster presented at the Deep Learning Indaba 2023 by Stephen Kiilu