2018.iwslt-1.12@ACL

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#1 The University of Helsinki submissions to the IWSLT 2018 low-resource translation task [PDF] [Copy] [Kimi1]

Author: Yves Scherrer

This paper presents the University of Helsinki submissions to the Basque–English low-resource translation task. Our primary system is a standard bilingual Transformer system, trained on the available parallel data and various types of synthetic data. We describe the creation of the synthetic datasets, some of which use a pivoting approach, in detail. One of our contrastive submissions is a multilingual model trained on comparable data, but without the synthesized parts. Our bilingual model with synthetic data performed best, obtaining 25.25 BLEU on the test data.