主催: The Japanese Society for Artificial Intelligence
会議名: 2019年度人工知能学会全国大会(第33回)
回次: 33
開催地: 新潟県新潟市 朱鷺メッセ
開催日: 2019/06/04 - 2019/06/07
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.