Difference between revisions of "Evaluation"
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==Using apertium-eval-translator for WER and PER== |
==Using apertium-eval-translator for WER and PER== |
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[http://svn.code.sf.net/p/apertium/svn/trunk/apertium-eval-translator/ apertium-eval-translator] is a script written in Perl. It calculates the word error rate (WER) and the position-independent word error rate (PER) between a translation performed by an Apertium-based MT system and its human-corrected translation at document level. Although it has been designed to evaluate Apertium-based systems, it can be easily adapted to evaluate other MT systems. |
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To use it, first translate a text with apertium, save that into <code>MT.txt</code>, then manually post-edit that so it looks understandable and grammatical (but trying to avoid major rewrites), save that into <code>postedit.txt</code>. Then run <code>apertium-eval-translator -test MT.txt -ref postedit.txt</code> and you'll see a bunch of numbers indicating how good the translation was, for post-editing. |
To use it, first translate a text with apertium, save that into <code>MT.txt</code>, then manually post-edit that so it looks understandable and grammatical (but trying to avoid major rewrites), save that into <code>postedit.txt</code>. Then run <code>apertium-eval-translator -test MT.txt -ref postedit.txt</code> and you'll see a bunch of numbers indicating how good the translation was, for post-editing. |
Revision as of 17:13, 14 March 2018
Evaluation can give you some idea as to how well a language pair works in practice. There are many ways to evaluate, and the test chosen should depend on the intended use of the language pair:
- how many words need to be changed before a text is publication-ready (Word-Error Rate, see Wikipedia on WER), here lower scores are better
- how many word N-gram's are common to the MT output and one or more reference translations (see Wikipedia on Bleu or NIST), here higher scores are better
- how many character N-gram's are common to MT output and a post-edit (the Fuzzy Match score, an unordered comparison with the Sørensen–Dice coefficient).[1]
- or the Character N-gram F-score (code at https://github.com/Waino/chrF)
- how well a user understands the message of the original text (this typically requires an experiment with real human subjects, see Assimilation Evaluation Toolkit).
Most released language pairs have had some evaluation, see Quality for a per-pair summary.
Using apertium-eval-translator for WER and PER
apertium-eval-translator is a script written in Perl. It calculates the word error rate (WER) and the position-independent word error rate (PER) between a translation performed by an Apertium-based MT system and its human-corrected translation at document level. Although it has been designed to evaluate Apertium-based systems, it can be easily adapted to evaluate other MT systems.
To use it, first translate a text with apertium, save that into MT.txt
, then manually post-edit that so it looks understandable and grammatical (but trying to avoid major rewrites), save that into postedit.txt
. Then run apertium-eval-translator -test MT.txt -ref postedit.txt
and you'll see a bunch of numbers indicating how good the translation was, for post-editing.
Detailed usage
apertium-eval-translator -test testfile -ref reffile [-beam <n>] Options: -test|-t Specify the file with the translation to evaluate -ref|-r Specify the file with the reference translation -beam|-b Perform a beam search by looking only to the <n> previous and <n> posterior neigboring words (optional parameter to make the evaluation much faster) -help|-h Show this help message -version|-v Show version information and exit Note: The <n> value provided with -beam is language-pair dependent. The closer the languages involved are, the lesser <n> can be without affecting the evaluation results. This parameter only affects the WER evaluation. Note: Reference translation MUST have no unknown-word marks, even if they are free rides. This software calculates (at document level) the word error rate (WER) and the postion-independent word error rate (PER) between a translation performed by the Apertium MT system and a reference translation obtained by post-editing the system ouput. It is assumed that unknow words are marked with a start (*), as Apertium does; nevertheless, it can be easily adapted to evaluate other MT systems that do not mark unknown words with a star.
See English and Esperanto/Evaluation for an example. In Northern Sámi and Norwegian there is a Makefile to translate a set of source-language files and then run the evaluation on them.
dwdiff
If you just need a quick-and-dirty PER (position-independent WER) test, you can use dwdiff -s reference.txt MT_output.txt
and look for % changed.
Pair bootstrap resampling
Evaluating with Wikipedia
- Main article: Evaluating with Wikipedia
See also
- Assimilation Evaluation Toolkit / Ideas for Google Summer of Code/Apertium assimilation evaluation toolkit
- Regression testing
- Quality control
- Calculating coverage
External links