蔡佳,王向东,唐李真,崔晓娟,刘宏,钱跃良. 基于汉盲对照语料库和深度学习的汉盲自动转换[J]. 中文信息学报, 2019, 33(4): 60-67.
CAI Jia, WANG Xiangdong, TANG Lizhen, CUI Xiaojuan, LIU Hong, QIAN Yueliang. A Deep Learning Method for Chinese-Braille Conversion Based onParallel Corpora. , 2019, 33(4): 60-67.
A Deep Learning Method for Chinese-Braille Conversion Based onParallel Corpora
CAI Jia1,2, WANG Xiangdong1, TANG Lizhen3, CUI Xiaojuan1,2, LIU Hong1, QIAN Yueliang1
1.Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; 2.University of Chinese Academy of Sciences, Beijing 100049, China; 3.China Braille Press, Beijing 100142, China
Abstract：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.
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2019, Vol. 33 
