If you look at the new count, the fuzzy matches (not internal) are still the same as in the previous count, but the number of new words has been reduced due to the internal fuzzy matches that have been recognised. As we have not ticked the Include Internal Fuzzy matches as TM Matches box, the internal fuzzy matches appear separately, at the top of the count. In this case we should always specify the minimum percentage range above which we want the tool to consider fuzzy matches as such, as opposed to new text. Count calculating the internal fuzzy matches separately.By way of an example, we tested two files and a local memory and this was the result: This is a very simple count, but it does not represent the true count, because you can normally take advantage of fuzzy matches between files from the same project. This way, not only does the system ignore internal repetitions, it also ignores internal matches. Count without calculating internal fuzzy matches.When you have dragged the txml file(s) to the box, you have to select the translation memory that you are going to use for the count, and then one of the following three settings: When selecting the appropriate options to perform the count, you have to consider how you want the different fuzzy matches to be displayed.
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This tab from the PM perspective in Wordfast Pro allows you to perform counts with TXML files, either with an online memory or a local memory.
Today I will be focusing on two other key functions, one for before you start working on a file and the other to complete the entire translation and review process. Hi everyone! Continuing with the theme of the first chapter of this post that I published in March this year, in this second article on using Wordfast Pro I will continue to talk about some of the tool’s options and how they help or affect the work of a project manager in a translation company.
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