CUNI Systems for the Unsupervised News Translation Task in WMT 2019

• DOI: 10.48550/arxiv.1907.12664
• Publication Date: 2019-01-01
• Authors: Ivana Kvapilíková; Dominik Macháček; Ondřej Bojar
• Keywords: Phrase; Table (database); Speech translation; BLEU

In this paper we describe the CUNI translation system used for unsupervised news shared task of ACL 2019 Fourth Conference on Machine Translation (WMT19). We follow strategy Artexte et al. (2018b), creating a seed phrase-based where phrase table is initialized from cross-lingual embedding mappings trained monolingual data, followed by neural machine synthetic parallel data. The corpus was produced tuned PBMT model refined through iterative back-translation. further focus handling named entities, i.e. part vocabulary mapping suffers most. Our reaches BLEU score 15.3 German-Czech WMT19 task.