首先感谢这位博主的文章
https://blog.youkuaiyun.com/liuy9803/article/details/104725092/
这里对这篇博客做了些补充和填坑工作。
首先从官网下载mteval-v14c
从中找到mteval-v14.pl文件
或者在这里下载mteval-v14.pl
然后使用按顺序下载以下几个库,下载后解压
XML-Twing https://metacpan.org/release/XML-Twig
expat-devel http://sourceforge.net/projects/expat/
XML-Parser https://metacpan.org/pod/XML::Parser
Sort-Naturally https://metacpan.org/pod/Sort::Naturally
String-Util https://metacpan.org/pod/String::Util
对于来自metacpan的库运行命令
perl Makefile.PL -y
make
make install
关于expat-devel 的安装
我们打开http://sourceforge.net/projects/expat/
直接点击download可能会下载zip后缀的win系统使用的expat,我的系统是Ubuntu,因此我下载后缀为.tar.gz的压缩包
下载后解压,执行以下命令
./configure
make
make install
如果make出现报错,尝试使用后再进行make
autoconf -ivf
下载这个博客中的python代码并将其命名为xml_transform.py
https://blog.youkuaiyun.com/angus_monroe/article/details/82943162
使用:
例:计算某个机器翻译模型的得分
把以下文件装在一个文件夹下
pred.txt # 模型预测结果
true.txt # 真实数据
mteval-v14.pl
xml_transform.py
依次执行以下命令
python xml_transform.py src text true pred true.txt
python xml_transform.py ref text true pred true.txt
python xml_transform.py tst text true pred pred.txt
perl mteval-v14.pl -s text_src.xml -r text_ref.xml -t text_tst.xml
最后得到结果
MT evaluation scorer began on 2022 Feb 18 at 22:33:13
command line: mteval-v14.pl -s text_src.xml -r text_ref.xml -t text_tst.xml
Evaluation of true-to-pred translation using:
src set "text" (1 docs, 1 segs)
ref set "text" (1 refs)
tst set "text" (1 systems)
NIST score = 2.3219 BLEU score = 0.1597 for system "pred"
# ------------------------------------------------------------------------
Individual N-gram scoring
1-gram 2-gram 3-gram 4-gram 5-gram 6-gram 7-gram 8-gram 9-gram
------ ------ ------ ------ ------ ------ ------ ------ ------
NIST: 2.3219 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 "pred"
BLEU: 1.0000 0.1250 0.0833 0.0625 0.0625 1.0000 1.0000 1.0000 1.0000 "pred"
# ------------------------------------------------------------------------
Cumulative N-gram scoring
1-gram 2-gram 3-gram 4-gram 5-gram 6-gram 7-gram 8-gram 9-gram
------ ------ ------ ------ ------ ------ ------ ------ ------
NIST: 2.3219 2.3219 2.3219 2.3219 2.3219 2.3219 2.3219 2.3219 2.3219 "pred"
BLEU: 1.0000 0.3536 0.2184 0.1597 0.1324 0.1855 0.2359 0.2826 0.3252 "pred"
MT evaluation scorer ended on 2022 Feb 18 at 22:33:13