上海交通大学学报(英文版) ›› 2017, Vol. 22 ›› Issue (1): 82-086.doi: 10.1007/s12204-017-1804-x
WANG Xiangdong1,3* (王向东), YANG Yang2 (杨阳), ZHANG Jinchao3 (张金超), JIANG Wenbin3 (姜文斌), LIU Hong1,3 (刘 宏), QIAN Yueliang1,3 (钱跃良
WANG Xiangdong1,3* (王向东), YANG Yang2 (杨阳), ZHANG Jinchao3 (张金超), JIANG Wenbin3 (姜文斌), LIU Hong1,3 (刘 宏), QIAN Yueliang1,3 (钱跃良
摘要: Automatic translation of Chinese text to Chinese Braille is important for blind people in China to acquire information using computers or smart phones. In this paper, a novel scheme of Chinese-Braille translation is proposed. Under the scheme, a Braille word segmentation model based on statistical machine learning is trained on a Braille corpus, and Braille word segmentation is carried out using the statistical model directly without the stage of Chinese word segmentation. This method avoids establishing rules concerning syntactic and semantic information and uses statistical model to learn the rules stealthily and automatically. To further improve the performance, an algorithm of fusing the results of Chinese word segmentation and Braille word segmentation is also proposed. Our results show that the proposed method achieves accuracy of 92.81% for Braille word segmentation and considerably outperforms current approaches using the segmentation-merging scheme.
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