Abstract
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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Acknowledgment
The authors thank TANG Lizhen, WO Shu-ping, HE Chuan, HAN Meng and others with the China Braille Publishing House as Braille experts.
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Foundation item: the National Key Technology R&D Program of China (No. 2014BAK15B02) and the National Natural Science Foundation of China (No. 61202209)
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Wang, X., Yang, Y., Zhang, J. et al. Chinese to Braille translation based on Braille word segmentation using statistical model. J. Shanghai Jiaotong Univ. (Sci.) 22, 82–86 (2017). https://doi.org/10.1007/s12204-017-1804-x
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DOI: https://doi.org/10.1007/s12204-017-1804-x