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English and Italian/Google Translate

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A basic evaluation of the Google Translate translation from English to Italian was made on 2014-03-20 according to Evaluation instructions and apertium-eval-translator.pl from latest trunk. We found a 21.63 % WER.

[edit] Method

As a base we used about 1000 words of an English leaflet (originally translated from German, which accounts for some peculiarities) by Wikimedia and Creative Commons (which accounts for some specialized terminology): Google Translate, manual corrections.

Considerations:

  • only agrammatical passages and turns of grammatical meaning were corrected,
  • as well as some inconsistencies in translation and major lexical errors which didn't convey the original meaning at all;
  • but errors which would not be evident without knowing the source were left alone, as well as lexical choices which are disputable but not outright wrong,
  • and the text wasn't made as fluent as it would be required to completely cover the machine translation origin.

The second result was calculated after removing the whitespace incorrectly added around punctuation; the difference is very significant, confirming our choice not to correct such whitespace errors to avoid excess noise in the evaluation.

Qualitative evaluation: anecdotically speaking, responsible translators often say that adjusting a Google Translation often takes more time and effort than translating on your own, because the meaning twists and errors of all sorts are often catastrophic, so you need to check the source language continuously and the track chosen by the machine is often the steepest one to follow. Mostly, one saves time by not having to open a dictionary dozens or hundreds times.

[edit] First revision

Common errors found:

  • missing concordance of singular/plural and male/female between noun and adjective/pronoun;
  • articles, especially definite article vs. no article;
  • co-ordinated sentences and pronouns (those... who and the like).
$ perl apertium-eval-translator.pl -test MT.txt -ref postedit.txt
Test file: 'MT.txt'
Reference file 'postedit.txt'

Statistics about input files
-------------------------------------------------------
Number of words in reference: 994
Number of words in test: 984
Number of unknown words (marked with a star) in test: 
Percentage of unknown words: 0.00 %

Results when removing unknown-word marks (stars)
-------------------------------------------------------
Edit distance: 215
Word error rate (WER): 21.63 %
Number of position-independent correct words: 862
Position-independent word error rate (PER): 13.28 %

Results when unknown-word marks (stars) are not removed
-------------------------------------------------------
Edit distance: 215
Word Error Rate (WER): 21.63 %
Number of position-independent correct words: 862
Position-independent word error rate (PER): 13.28 %

Statistics about the translation of unknown words
-------------------------------------------------------
Number of unknown words which were free rides: 0
Percentage of unknown words that were free rides: 0%

[edit] Second revision

$ perl apertium-eval-translator.pl -test MT.txt -ref postedit.txt
Test file: 'MT.txt'
Reference file 'postedit.txt'

Statistics about input files
-------------------------------------------------------
Number of words in reference: 915
Number of words in test: 984
Number of unknown words (marked with a star) in test: 
Percentage of unknown words: 0.00 %

Results when removing unknown-word marks (stars)
-------------------------------------------------------
Edit distance: 345
Word error rate (WER): 37.70 %
Number of position-independent correct words: 719
Position-independent word error rate (PER): 28.96 %

Results when unknown-word marks (stars) are not removed
-------------------------------------------------------
Edit distance: 345
Word Error Rate (WER): 37.70 %
Number of position-independent correct words: 719
Position-independent word error rate (PER): 28.96 %

Statistics about the translation of unknown words
-------------------------------------------------------
Number of unknown words which were free rides: 0
Percentage of unknown words that were free rides: 0%
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