Neural Machine Translation for African Languages
Project description
Ukuxhumana
"Ukuxhumana" means "Communicate" in Zulu. This project is aimed at exploring ideas for using Neural Machine Translation for low-resource languages - specifically for the official languages of South Africa.
Data
Parallel Corpuses
Our parallel corpuses are from the Autshumato project. The datasets contain data that was translated by professional translators, data that was sourced as translated file pairs from translators and data obtained from Government websites and documents
Models
Two main architectures are used throughout this project, namely Convolutional Sequence to Sequence by Gehring et. al. and Transformer by Vaswani et. al. Fairseq(-py) and Tensor2Tensor were used in modeling these techniques respectively.
Results
Results are given in BLEU.
Baseline
English -> Language
Model | Setswana | isiZulu | Northern Sotho | Xitsonga | Afrikaans |
---|---|---|---|---|---|
Convolutional Seq2Seq | 27.77 (24.18) | 0.62 (0.28) | 15.35 (7.41) | 36.96 | 16.17 |
Convolutional Seq2Seq (40K BPE) | 23.83 | 1.44 | 4.89 | 34.28 | 21.06 |
Convolutional Seq2Seq (8K BPE) | 2.19 | 15.45 | 26.78 | ||
Transformer (uncased) | 33.53 | 4.55 | 29.23 | 47.37 | 35.26 |
Transformer (cased) | 33.12 | 4.45 | 28.71 | 46.95 | 34.81 |
Transformer (40k BPE) (uncased) | 4.29 | ||||
Transformer (40k BPE) (cased) | 4.14 | ||||
Transformer (8k BPE) (uncased) | |||||
Transformer (8k BPE) (cased) |
Language -> English
Model | Setswana | isiZulu | Northern Sotho | Xitsonga | Afrikaans |
---|---|---|---|---|---|
Convolutional Seq2Seq | |||||
Transformer (uncased) | |||||
Transformer (cased) |
Project details
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