how adaptiveWords and baselineWords change their values in Studio 2017 analyses to non-zero

I would need some documentation about how do some 2017 report numbers work in analyses. Read, how do numbers of both "AdaptiveMT Baseline" and "Adaptive MT with Learnings" show up and the process behind. I've tried connecting LC but I see those values again set to zero after my test analysis. As we need to map those numbers to our erp system, I'd like to know how and when they become <> 0 (I assume a simple and informative subset of New/AT? Just like tokens for their reference lines, right?). Is there any specific documentation for that? I've only found what they are basically, but I can't figure out how and the reason behind their change from 0 to something different because this will affect the way the system is picking them up. The xml line I'm referring to is adaptiveWords="0" baselineWords="0". At the end and in a nutshell, I need a way to repro a change of their values.
Best, Matteo Rozzarin

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  • Hi Cesare,

    To populate these figures shouldn't be too hard.  Just create an adaptive engine and then analyse your files.  I did this and see this for example:

    I then go through the translation a little, with no TM as I am only working with the AdaptiveMT and after correcting a few here and there I clear the translation completely and then re-analyse with this same adaptive engine (note I only worked on a few segments out of the whole file):

    This time I can see the benefit of using the adaptiveMT as it's taking into account where an improved translation would have been used.

    However, having said this it's still MT and the translation could still be wrong.  In my example some of it will be perfect I hope because I have used it on the same document as if I was doing it from scratch, but some may be where the engine now thinks it can use what it has learned in a different context.  It may well be better, but it may not be.  So this analysis is only a guide to give you some idea of the benefits you may be getting through using the adaptive engines.  If your translators complain that the results are just as bad then it can help you identify texts to test with and see who things could be improved.  So used in conjunction with a tool like Qualitivity for example this can be a very useful piece of intelligence to help improve the engines and the post-editing process.  If you haven't used that tool this article might be wort a read:

    multifarious.filkin.com/.../

    Regards

    Paul

    Paul Filkin | RWS Group

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  • Hi Paul,
    got your point, and could see the numbers shifting from New/AT to the categories below, that was the process I needed to have clear actually. Thanks! Matteo
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