This repository provides guidelines for using our submission to the constrained track of the WMT22 Shared Task: Large-Scale Machine Translation Evaluation for African Languages. Our system is a single multilingual translation model that translates between English and 8 South / South East African Languages, as well as between specific pairs of the African languages.

Our system translates between English and 8 South / South East African languages (Afrikaans, Northern Sotho, Shona, Swati, Tswana, Xhosa, Xitsonga, Zulu) and in 8 additional directions (Xhosa to Zulu, Zulu to Shona, Shona to Afrikaans, Afrikaans to Swati, Swati to Tswana, Tswana to Xitsonga, Xitsonga to Northern Sotho, Northern Sotho to Xhosa).

• eng ⟷ afr, eng ⟷ nso, eng ⟷ sna, eng ⟷ ssw, eng ⟷ tsn, eng ⟷ xho, eng ⟷ tso, eng ⟷ zul.
• xho ⟶ zul, zul ⟶ sna, sna ⟶ afr, afr ⟶ ssw, ssw ⟶ tsn, tsn ⟶ tso, tso ⟶ nso, nso ⟶ xho.

We have two bash scripts for installing the required pachages and running the model:

1. setup_conda_env.sh

This creates a new conda env, installs the required packages, and downloads the model and other files needed to run our model.

bash setup_conda_env.sh

2. run_inference.sh

Given source sentences in a simple text file (one sentence per line), it runs our preprocessing pipeline and produces our model's translations of the sentences in a target language. This script should be run with the following command line arguments:

bash run_inference.sh <tgt> <src> <batch_size> <input_path> <output_path>.

For example:

bash run_inference.sh eng afr 8 afr.test eng.out

The output path eng.out will be a simple text file with one sentence per line, in the same order as the sentences appeared in the input path afr.test.