基于语义语法分析的中文语句困惑度评价

发布时间：2018-04-26 00:38

  本文选题：困惑度 + 病句　； 参考：《计算机应用研究》2017年12期

【摘要】：目前用来评价机器翻译系统译文质量的方法主要有IBM提出的BLEU、TER和METEOR等方法,分别以词汇的重现率、译文与参考译文之间的编辑距离和语言学知识等特征作为评价依据,在判定中文句子的困惑度方面具有一定局限性。提出在依存语法分析的基础上,通过对中文句子及其句子主干的语法和语义两方面进行分析得出中文句子的困惑度。实验证明这种方法比通过译文加权改进后的BLEU方法准确率高出4%。
[Abstract]:At present, the methods used to evaluate the quality of the Machine Translation system mainly include the methods of BLEU, TER and METEOR proposed by IBM, which are based on the repetition rate of vocabulary, the editing distance between the translation and the reference translation and the linguistic knowledge, and have some limitations in determining the confusion of Chinese sentences. On the basis of grammatical analysis, the perplexity of Chinese sentences is obtained by analyzing the two aspects of the grammar and semantics of the Chinese sentence and the main sentence of the sentence. The experiment proves that this method is more accurate than the BLEU method which is improved by the translation weighted 4%..

【作者单位】： 山东师范大学信息科学与工程学院;山东省分布式计算软件新技术重点实验室;
【基金】：国家自然科学基金资助项目(61672329,61373149,61472233,61572300,81273704) 山东省科技计划资助项目(2014GGX101026) 山东省教育科学规划资助项目(ZK1437B010) 山东省泰山学者基金资助项目(TSHW201502038,20110819) 山东省精品课程资助项目(2012BK294,2013BK399,2013BK402)
【分类号】：TP391.1
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本文编号：1803728