Difference between revisions of "Automatic postediting at GSoC 2018"
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==== Code refactoring ==== |
==== Code refactoring ==== |
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Two old scripts, ''learn_postedits.py'' and ''apply_postedits.py'' were refactored. Also now both scripts work approximately 10 times faster: now scripts collect all subsegments in one large file and translate/analyze the whole file. Instead of calling Apertium few times for every subsegment, now it is called only two times (for translating and for analyzing) for all subsegments of a sentence. |
Two old scripts, ''learn_postedits.py'' and ''apply_postedits.py'' were refactored. Also now both scripts work approximately 10 times faster: now scripts collect all subsegments in one large file and translate/analyze the whole file. Instead of calling Apertium few times for every subsegment, now it is called only two times (for translating and for analyzing) for all subsegments of a sentence. |
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| + | ==== Operations extraction ==== |
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| + | There were three attempts to extract postediting operations for each language pair: with threshold = 0.8 and -m, -M = (1, 3). |
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| + | In fact, results are not very meaningful: the reason might lie in problems in ''learn_postedits.py'' and in the method itself (but it should be checked carefully). |
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Revision as of 23:33, 11 June 2018
Contents
Related links
https://github.com/deltamachine/naive-automatic-postediting
Workplan
| Week | Dates | To do |
|---|---|---|
| 1 | 14th May — 20th May | |
| 2 | 21th May - 27th May | |
| 3 | 28th May — 3rd June | |
| 4 | 4th June — 10th June | Work on the old code, start to extract triplets. |
| First evaluation, 11th June - 15th June | ||
| 5 | 11th June — 17th June | |
| 6 | 18th Jule — 24th July | |
| 7 | 25th July — 1st July | |
| 8 | 2nd July — 8th July | |
| Second evaluation, 9th July - 13th July | ||
| 9 | 9th July — 15th July | |
| 10 | 16th July — 22th July | |
| 11 | 23rd July — 29th July | |
| 12 | 30th August — 5th August | |
| Final evaluation, 6th August - 14th August | ||
Progress notes
Data preparation
Russian - Belarusian
- Mediawiki: 2059 sentences - source, Apertium translated and postedited by humans (only bel -> rus)
- Tatoeba: 1762 sentences: source, target and both ways Apertium translated (bel -> rus, rus -> bel)
Total amount of sentences: 3821.
Russian - Ukranian
- Tatoeba: 6463 sentences - source, target and both ways Apertium translated (ukr -> rus, rus -> ukr)
- OpenSubtitles: 2000 manually filtered and corrected source - target pairs from OpenSubtitles2018 corpora preprocessed with bicleaner + both ways Apertium translations (ukr -> rus, rus -> ukr).
Total amount of sentences: 8463.
Code refactoring
Two old scripts, learn_postedits.py and apply_postedits.py were refactored. Also now both scripts work approximately 10 times faster: now scripts collect all subsegments in one large file and translate/analyze the whole file. Instead of calling Apertium few times for every subsegment, now it is called only two times (for translating and for analyzing) for all subsegments of a sentence.
Operations extraction
There were three attempts to extract postediting operations for each language pair: with threshold = 0.8 and -m, -M = (1, 3). In fact, results are not very meaningful: the reason might lie in problems in learn_postedits.py and in the method itself (but it should be checked carefully).
