The post-editing analysis in Memsource Cloud extends the traditional translation memory analysis to also include machine translation (MT) and non-translatables (NT).
When a user clicks in a segment, the current translation memory, machine translation, and/or non-translatable match gets saved for that segment and is later used to calculate the post-editing analysis.
The post-editing analysis is based on the target, therefore it must be launched after the post-editing job has been completed.
Analyze TM post-editing
The Analyze TM post-editing option is used for calculating the post-editing effort for matches from the translation memory (TM).
Analysis with Analyze TM post-editing enabled:
- Intended for a low-quality TM that can contain high percent matches that need to be heavily edited by the linguist.
- Analysis will show the post-editing effort for the translation memory, machine translation, and non-translatables.
- There are only 100% matches in the analysis (in-context 101% matches from TM have no effect on the calculation).
- A 100% match from the TM can become 0% if completely edited by the linguist.
- Any match from the TM can become a 100% match if accepted by the linguist without any change.
Analysis with Analyze TM post-editing disabled:
- Intended for a high-quality TM where the matches should be edited as little as possible, to keep the cost low.
- The analysis will show 101% and 100% (similar to Default analysis)
- The analysis will show TM matches offered to the linguist when the segment opened (not the actual linguist's post-editing effort)
- The analysis will show the post-editing effort for machine translation and non-translatables.
Machine translation and Non-translatables
Regardless of the Analyze TM post-editing settings, the MT and NT results will always show post-editing effort for each segment. It reflects the changes made by the linguist compared to the MT and NT suggestions.
- If the MT or NT suggestion was accepted without further editing (the linguist did not need to change it at all), it would come up as a 100% match in the analysis.
- If, on the other hand, the linguist changes the MT or NT heavily, the match rate will be close to 0%. The score counting algorithm is identical to the one that we use to calculate the score of translation memory fuzzy matches.
Example of Post-editing analysis with disabled "Analyze TM post-editing" option: