Machine Translation
CAI Jia, WANG Xiangdong, TANG Lizhen, CUI Xiaojuan, LIU Hong, QIAN Yueliang
2019, 33(4): 60-67.
The Chinese-Braille conversion can be applied to fields such as Braille publication, education for the blind, etc. This paper presents a deep learning solution to automatic Chinese-Braille conversion based on parallel corpora. A Bi-directional LSTM model is trained using segmented Chinese texts according to the Braille segmentation rules and achieves high accuracy of Braille word segmentation. In order to support the model training, this paper also presents a strategy of automatically generating a corpus from Chinese and braille texts with the same content, with alignments at article-level, sentence-level and word-level, totaling 270 000 sentences, 2.34 million Chinese characters, and 4.48 million Braille symbols. The experimental results show that the proposed method outperforms the existing models.