CLMar 9, 2020
Tigrinya Neural Machine Translation with Transfer Learning for Humanitarian Response
arXiv:2003.11523v113 citationsHas Code
AI Analysis
This work addresses the need for improved translation tools for Tigrinya in humanitarian response contexts, though it is incremental in nature.
The researchers tackled the problem of domain-specific Tigrinya-to-English neural machine translation by using transfer learning from other Ge'ez script languages, achieving an improvement of 1.3 BLEU points over a classic neural baseline.
We report our experiments in building a domain-specific Tigrinya-to-English neural machine translation system. We use transfer learning from other Ge'ez script languages and report an improvement of 1.3 BLEU points over a classic neural baseline. We publish our development pipeline as an open-source library and also provide a demonstration application.