Word Reordering as a Preprocessor for Machine Translation Systems

机译：作为机器翻译系统的预处理器重新排序

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摘要

Existing machine translation systems work well when the structures of both the source and target languages are similar. Generally, Indian languages follow Subject-Object-Verbstructure. When translating English sentences to Indian languages, we propose that reordering the sentences to SOV as a preprocessing step will improve the performance of the translation.

机译：当源语言和目标语言的结构相似时，现有的机器翻译系统很好。通常，印度语言遵循主题对象逆情。在将英语句子转换为印度语言时，我们建议将SOV的句子重新排序为预处理步骤将提高翻译的性能。

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《International Conference on Inventive Systems and Control》|2017年|884p|共4页
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作者
R. N. Devendrakumar; A. Praveena;
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中图分类 TP2-53;
关键词
Word Reordering; Indian Languages; Machine Translation;

机译：重新排序;印度语言;机器翻译;

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Word Reordering as a Preprocessor for Machine Translation Systems

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