How to improve TM suggestions on Crowdin?

Hi folks! I have rather interesting question regarding TMs’ suggestions. We have a lot of strings with various tags in it, some of them are just symbols, but the other ones include metadata or numeric values. So, the TM suggestions work perfectly with the first type of strings, but with the other type we always get those annoying 92-97% of match (which as you know can’t be pre-translated). Do you happen to know is there a chance to improve the TM matches?

Just for the reference: String A - text{{7890VALUE}}, String B - text{{0123VALUE}}. Whenever we translate the string A, the match for the string B is always a bit off. Looking forward to your suggestions!


Hi! I think I know a perfect solution for you, I’m using it on my Open Source project - the one and only “Auto-Substitution” :smiley:

This feauture automatically uses the closest TM match and adjusts it to the similar source string. In other words it can make the 93% match easily a 100% match. I assume in your case it will take the translation from the string A and replace the numeric value in the translation to match the string B (I hope I’m not mistaken)

You can try it on your own, perhaps it will suit your needs just perfectly
P.S. Just in case - The option could be found in the General settings :slight_smile: