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引用次数: 3
摘要
本文基于ConceptNet for Statistical Machine translation和基于规则的机器翻译系统(Rule-Based Machine translation system)对英语句子进行北印度语翻译的框架。ConceptNet是一个基于知识的图表,它使用“RelatedTo”和“TranslatedFrom”这样的关系来表示单词之间的关系。基线方法不能正确翻译句子。这项工作通过使用常识知识来翻译那些模糊或未翻译的单词,提高了翻译的准确性。我们使用BLEU分数来检查我们的英语到印度语翻译系统的准确性。这种方法提高了翻译质量。
Improvement of English-Hindi machine translation using ConceptNet
The paper is based on the framework of translation of English sentences into Hindi language by using ConceptNet for Statistical Machine Translation and Rule-Based Machine Translation system together. ConceptNet is a knowledge-based graph that represents relation between words using relations like “RelatedTo” and “TranslatedFrom”. Baseline method doesn't appropriately translate the sentences. This work increases the accuracy of translation by using common sense knowledge for translation of those words which are obscured or not translated. We used BLEU score to check the accuracy of our English to Hindi translation system. This approach provides the improved quality of translation.