Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation
Table 5: Test BLEU for High/Medium/Low (High/Med/Low) resource language pairs in many-to-many setting on OPUS-100 (100 languages). We report average BLEU for each category.
['ID', 'Model Architecture', '[ITALIC] L', '#Param', 'English→X High', 'English→X Med', 'English→X Low', 'X→English High', 'X→English Med', 'X→English Low']
Our multilingual training data is distributed unevenly across different language pairs, which could affect the knowledge transfer delivered by language-aware modeling and deep Transformer in multilingual translation. We investigate this effect by grouping different language pairs in OPUS-100 into three categories according to their training data size: High (≥0.9M, 45), Low (<0.1M, 18) and Medium (others, 31).