2020/11/10 by Ife Adebara, Adebara, Ife, El Moatez Billah Nagoudi +3
Computer Science · #Natural Language Processing Techniques #Speech and dialogue systems
paper · pdf · doi:10.48550/arxiv.2011.05037
We investigate different approaches to translate between similar languages\nunder low resource conditions, as part of our contribution to the WMT 2020\nSimilar Languages Translation Shared Task. We submitted Transformer-based\nbilingual and multilingual systems for all language pairs, in the two\ndirections. We also leverage back-translation for one of the language pairs,\nacquiring an improvement of more than 3 BLEU points. We interpret our results\nin light of the degree of mutual intelligibility (based on Jaccard similarity)\nbetween each pair, finding a positive correlation between mutual\nintelligibility and model performance. Our Spanish-Catalan model has the best\nperformance of all the five language pairs. Except for the case of\nHindi-Marathi, our bilingual models achieve better performance than the\nmultilingual models on all pairs.\n