@inproceedings{27583692ed1c403da039fa79aec76a1c,
title = "Extending BLEU evaluation method with linguistic weight",
abstract = "BLEU is one of the most popular metrics for automatic evaluation of machine translation quality. Focusing on its ignorance of different effects of various translation units upon translation quality, this paper extends proper weights to different words and n-grams in the framework of BLEU. The linear regression method is adopted to capture the human perception on translation quality via word types and n-gram length. Compared with other linguistic-rich metrics based on machine learning, the proposed approach is simple and largely preserves BLEU's advantage of language independence. Experimental results indicate that this method brings a much better evaluation performance for both human translation and machine translation than original BLEU.",
keywords = "BLEU, Linear regression, Linguistic weight, Machine translation evaluation",
author = "Muyun Yang and Junguo Zhu and Jufeng Li and Lixin Wang and Haoliang Qi and Sheng Li and Liu Daxin",
year = "2008",
doi = "10.1109/ICYCS.2008.362",
language = "英语",
isbn = "9780769533988",
series = "Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008",
pages = "1683--1688",
booktitle = "Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008",
note = "9th International Conference for Young Computer Scientists, ICYCS 2008 ; Conference date: 18-11-2008 Through 21-11-2008",
}