Benchmarking Neural Machine Translation for Southern African Languages

• DOI: 10.48550/arxiv.1906.10511
• Publication Date: 2019-01-01
• Authors: Laura Martinus; Jade Abbott
• Keywords: Benchmarking; Languages of Africa; Code (set theory)

Unlike major Western languages, most African languages are very low-resourced. Furthermore, the resources that do exist often scattered and difficult to obtain discover. As a result, data code for existing research has rarely been shared. This lead struggle reproduce reported results, few publicly available benchmarks machine translation models exist. To start address these problems, we trained neural 5 Southern on publicly-available datasets. Code is provided training evaluate newly released evaluation set, with aim of spur future in field languages.