2019年度 人工知能学会全国大会（第33回）
2019年6月4日〜6月7日朱鷺メッセ 新潟コンベンションセンター
2019年度 人工知能学会全国大会（第33回）
2019年6月4日〜6月7日朱鷺メッセ 新潟コンベンションセンター
[3B4-E-2-04]Application of Unsupervised NMT Technique to Japanese--Chinese Machine Translation
〇Yuting Zhao1, Longtu Zhang1, Mamoru Komachi1(1. Tokyo Metropolitan University)
Neural machine translation (NMT) often suffers in low-resource scenarios where sufficiently large-scale parallel corpora cannot be obtained. Therefore, a recent line of unsupervised NMT models based on monolingual corpus is emerging. In this work, we perform three sets of experiments that analyze the application of unsupervised NMT model in Japanese--Chinese machine translation. We report 30.13 BLEU points for ZH--JA and 23.42 BLEU points for JA--ZH.