Is there a way to fine tune settings to get better fuzzy matches?
Thread poster: Brent Sørensen

Brent Sørensen  Identity Verified
Germany
Local time: 01:53
Member (2016)
German to English
+ ...
Apr 16, 2020

Let's say that I have the following segment in my TM.
Although this is still considered an acceptable alternative name, most botanists now use the name Lamiaceae in referring to this family.

My new translation has the following segment:
1. Most botanists now use the name Lamiaceae in referring to this family.
2. This is still considered an acceptable name, and most botanists now use it when referring to this family.

Both would give fuzzy matches with a
... See more
Let's say that I have the following segment in my TM.
Although this is still considered an acceptable alternative name, most botanists now use the name Lamiaceae in referring to this family.

My new translation has the following segment:
1. Most botanists now use the name Lamiaceae in referring to this family.
2. This is still considered an acceptable name, and most botanists now use it when referring to this family.

Both would give fuzzy matches with a score of 70% or so. However, Segment 1 gives a much more useful fuzzy match. All I have to do is delete the first part of the sentence. For Segment 2, I will essentially have to translate from scratch, and it will not save me much time.

Is there any way that I can adjust the settings (possibly penalty settings) so that I will get only fuzzy matches of Type 1.
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Anthony Rudd

Local time: 01:53
German to English
+ ...
Better fuzzy match Apr 17, 2020

You could write a regex to do a "cleanup" and convert to a single name.

 

Brent Sørensen  Identity Verified
Germany
Local time: 01:53
Member (2016)
German to English
+ ...
TOPIC STARTER
Could you elaborate Apr 17, 2020

Hi Anthony,
Thanks for your response. Could you elaborate on that a bit?
Thanks,
Brent


 

DZiW (X)
Ukraine
English to Russian
+ ...
A per-project fitted value Apr 17, 2020

Brent, while certain language pairs combo may tend to specific fuzziness levels, CATs have different and proprietary formulae to calculate fuzzy matches (which is but Levenshtein/Edit distance modifications). To add to the confusion, texts in some fields and styles may be prone to fluctuation badly, so even with similar SVO-languages, I believe it’s a per-project value. Empirically... See more
Brent, while certain language pairs combo may tend to specific fuzziness levels, CATs have different and proprietary formulae to calculate fuzzy matches (which is but Levenshtein/Edit distance modifications). To add to the confusion, texts in some fields and styles may be prone to fluctuation badly, so even with similar SVO-languages, I believe it’s a per-project value. Empirically increase the fuzzy match threshold, eliminating too many false positives.

On the other hand, I think it’s not funny when translators have to waste their time on tweaking and struggling with the hardware or software instead of doing the job. Why should one make wild guesses and wait for a prompt (fuzzy match) already knowing the translation, I wonder?--Unless it’s about mimicking somebody else’s ‘uniformity’ guidelines, lex, and style, of course.
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Is there a way to fine tune settings to get better fuzzy matches?







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