AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages (2021.emnlp-main)
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| Challenge: | Existing reproducible benchmarks for machine translation are limited to high-resource or well-represented languages. |
| Approach: | They propose to use AfroMT to develop a reproducible machine translation benchmark for eight widely spoken African languages and a suite of analysis tools to take into account their unique properties. |
| Outcome: | The proposed benchmarks show significant improvements when pretraining on 11 languages, with gains of up to 2 BLEU points over strong baselines. |
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