计算机科学
盲文
机器翻译
Python(编程语言)
人工智能
程序设计语言
自然语言处理
人工神经网络
判决
同步上下文无关文法
基于实例的机器翻译
基于规则的机器翻译
翻译(生物学)
语音识别
操作系统
生物化学
化学
信使核糖核酸
基因
作者
Yuko Shimomura,Hiroyuki Kawabe,Hidetaka Nambo,Shuichi Seto
出处
期刊:Advances in intelligent systems and computing
日期:2019-06-19
卷期号:: 335-345
被引量:6
标识
DOI:10.1007/978-3-030-21248-3_25
摘要
We have constructed a translation system to use easily even for beginners. In order to translate Japanese into Braille, we programmed in Python and C language using MeCab, a morphological analysis engine. However, there are many exceptions in Braille grammar, and the programming has become complicated. In recent years, researches on the machine translation using a neural network are thriving, so we carried out braille translation using the technology of neural machine translation (NMT) this time. Tensorflow was used as a library of neural network. We also incorporated a transform which was a translation component in the open source library Tensor2Tensor. We used 100,000 words of Japanese as teacher data. By using NMT, the morphological engine and the complicated programming become unnecessary. Also, MNT can translate without worrying about the complex Braille grammar. Then, just by entering Japanese sentence, the Braille codes are output. There are many advantages. We describe the braille translation using NMT.
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