NDLI: Automatic Machine Translation Evaluation Based on Sentence Structure Information

Content Provider	IEEE Xplore Digital Library
Author	Ding Ze-ya Zang Han-fen Zhang Quan Miao Jian-ming Chi Yu-huan
Copyright Year	2009
Abstract	Automatic evaluation of machine translation plays an important role in improving the performance of machine translation systems. In this paper, we firstly introduce three traditional methods of automatic evaluation, including BLEU, NIST and WER. All these methods are based on surface layer information of translations like vocabularies, so we do some studies on the evaluation method using the information of sentence structure. Because the Hierarchical Network of Concepts (HNC) theory thinks that sentence category and format transformations are two most important links in machine translation, we do some researches about sentence category and format transformations, and get the sentence structure information which is composed of sentence category information and format information of every sentence in the bilingual (Chinese and English) translation corpora. Then, considering the traditional methods above, we propose the method of automatic evaluation based on the information of sentence structure and have proved it effective by experiment.
Starting Page	162
Ending Page	166
File Size	382669
Page Count	5
File Format	PDF
ISBN	9780769539041
DOI	10.1109/IALP.2009.42
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-07
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vocabulary Sentence Category Transfer Natural languages Humans NIST Acoustics Automatic Evaluation of Machine Translation Sentence structure information Statistics Information analysis Sentence Format Transfer
Content Type	Text
Resource Type	Article

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