使用深度学习的日文盲字翻译 - 从音声字符 (Kana) 转换为同名字符 (Kanji)
Shuichi Seto1, Hiroyuki Kawabe2, Yoko Shimomura3
1Department of Business Administration, Kinjo College, Hakusan, Japan.
Studies in health technology and informatics
|August 28, 2023
概括
这项研究开发了一个深度学习翻译器,将盲文报告转换为可读的Kana-Kanji句子,供教师使用. 该系统实现了高精度,提高了盲学生书面工作的可访问性.
科学领域:
- 人工智能的人工智能
- 自然语言处理自然语言处理.
- 辅助技术 辅助技术 辅助技术
背景情况:
- 盲人学生使用盲文文字处理器来撰写报告.
- 对于教育工作者来说,将盲文转写为文本是一项挑战,尤其是在 Kanji 的同名词方面.
- 现有的翻译方法与汉字的模两可而斗争.
研究的目的:
- 开发一个基于深度学习的翻译器,用于将盲文转换为混合的Kana-Kanji句子.
- 为了提高教师的盲文报告的可读性.
- 为了应对自动翻译中汉字同名词的挑战.
主要方法:
- 使用深度学习模型将盲文翻译为Kana-Kanji.
- 创建了一个培训数据集,包含15,000个盲人代码和Kana-Kanji句子对.
- 使用验证数据集来评估翻译准确性和识别错误.
主要成果:
- 获得了0.906的训练准确度和0.600的BLEU分数.
- 在100个句子的验证集中,鉴定了5个因同名词导致的错误汉字选择.
- 强调了汉字同名词解析的上下文依赖性.
结论:
- 深度学习有效地将盲文翻译为Kana-Kanji,而上下文对于同义词的明确性至关重要.
- 进一步改进需要更大的网络模型和段落级翻译.
- 扩大网络结构是必要的,以减少汉字同义词错误.
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