  Neural Machine Translation (NMT) has been proven to achieve impressive
results. The NMT system translation results depend strongly on the size and
quality of parallel corpora. Nevertheless, for many language pairs, no
rich-resource parallel corpora exist. As described in this paper, we propose a
corpus augmentation method by segmenting long sentences in a corpus using
back-translation and generating pseudo-parallel sentence pairs. The experiment
results of the Japanese-Chinese and Chinese-Japanese translation with
Japanese-Chinese scientific paper excerpt corpus (ASPEC-JC) show that the
method improves translation performance.
