El dt 18 de 03 de 2014 a les 14:30 -0700, en/na Alex Aruj va escriure:
> I ran into a section in wiki about testvoc which delineates a similar
> procedure to assess quality, so I will budget time in next 24 hours to
> learn how to identify the holes in the coverage with that tool
> (http://wiki.apertium.eu/index.php/Session_7). Also, I appreciate the
> follow-up on my battle to update dictionaries. I have to dive into
> that again and even testvoc, if possible tonight my time (PST). I will
> formally submit the application tomorrow, since I am not sure I will
> have internet at least through part of Friday. So, if the timeline
> looks too rough or downright unintelligible when reviewed, I hope I
> get the time to re-adjust it.

Cool!

> Here are my stats from a short file ~200 words I post-edited and
> compared with raw MT version. Earlier, I must have been running the
> apertium-eval-translator incorrectly on each set of four files. I have
> not found time to post-edit all. for my short 200-word file, the
> numbers are looking more reasonable:
> 
> 
> Test file: 'en-target2'
> Reference file 'en-target2-posted'
> 
> 
> Statistics about input files
> -------------------------------------------------------
> Number of words in reference: 187
> Number of words in test: 188
> Number of unknown words (marked with a star) in test: 14
> Percentage of unknown words: 7.45 %
> 
> 
> Results when removing unknown-word marks (stars)
> -------------------------------------------------------
> Edit distance: 66
> Word error rate (WER): 35.29 %
> Number of position-independent correct words: 137
> Position-independent word error rate (PER): 27.27 %

This looks more like it. So, the target for this task[1] is to reduce
the WERE by 30-50% the WER down to ~25-17% :)

F.

1.
http://wiki.apertium.org/wiki/Ideas_for_Google_Summer_of_Code/Make_a_language_pair_state-of-the-art



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