Post-editing Analysis

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The post-editing analysis in MemSource Cloud extends the traditional translation memory analysis to also include machine translation. It analyzes the MT post-editing effort for each segment and compares the machine translation output with the final post-edited translation (edit distance). Therefore, if the machine translation output 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 output 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. The only difference is that the post-editing analysis is based on the target. Therefore, the post-editing analysis must be, quite naturally, launched after the post-editing job has been completed.

A sample post-editing analysis: Post-editing-analysis.png


The post-editing analysis has two main components, which get combined together: The translation memory and machine translation analysis.

Machine Translation Analysis

Translation Memory Analysis

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