Annick Guldentops

There has never been a feature like this, even with the old statistical engines.

We are going to start work shortly on activating dictionary support via the user interface for the SDL MT Cloud plugin but this won't use a termbase directly, at least not in the initial implementation.  It will use the dictionaries that are available as part of an SDL MT Cloud account.

Annick Guldentops

There has never been a feature like this, even with the old statistical engines.

We are going to start work shortly on activating dictionary support via the user interface for the SDL MT Cloud plugin but this won't use a termbase directly, at least not in the initial implementation.  It will use the dictionaries that are available as part of an SDL MT Cloud account.

OK, that would be great to start with. 

Sorry for the late reply; I just joined the community and I forgot to reply to the confirmation email – now, a week later, the email is no longer valid I think. How do I solve that?

Annick Guldentops

I don't think you have to do anything... it looks like you have one account and it seems to work or you would not be able to post.

Thanks Paul. Everything is working fine – I was looking in the wrong group.

And of course, looking forward to any new developments to get terms into the NMT suggestions to make them even better ;-)

Paul

I thought I remembered uploading my TermBase to LC and getting TermBase entries back in my translations... That was before "custom termbase format" became restricted to business users...

Daniel

Unknown said:

I thought I remembered uploading my TermBase to LC and getting TermBase entries back in my translations

Perhaps you recall the adaptive MT where it could learn from what you entered as the translation?  So if you enforced a particular term after a while it would be used.

Yes, it did that, too, but I could also upload a TB:

I can't get this to work now, but I seem to remember it worked a year ago. Pretty sure I used an adaptive MT with term replacement based on an uploaded TB.

Daniel

Hi Daniel, hi Paul,

I have asked a similar question - termbase upload/dictionary use with SMT engines worked, but now for NMT engines, there seems to be only a paid solution, see the answers from Dusan Halamka  and Quinn Lam in https://community.sdl.com/product-groups/machine_translation/f/forum/28029/corrupted-words-with-nmt-engine

Kind regards

Christine

Thanks Christine Bruckner

as pointed out in the thread you mentioned: "SDL Language Cloud provider does provide Dictionary support, but it is for SMT (Statistical MT) and soon to be deprecated." (emphasis is mine)

This was written two months ago... maybe that explains why using Termbases worked last year and does not seem to work anymore.

I think that USP of SDL's MT solutions has to be integration with Studio and Multiterm, as the MT market is pretty competitive, so I would love to see a terminology option for LC.

Daniel

Hi Daniel,

the dictionary feature for SMT was just a brute-force search & replace of terms coming from the uploaded termbase - not linguistic or artificial intelligence involved. This rather deteriorated the (S)MT results, especially if the termbase/glossary was uploaded "as is" without any cleanup.

So I hope that the terminology option of NMT is more refined - tackling the terminology challenge in NMT is not easy, but SDL seems to have done some in-depth research.

Kind regards

Christine

 Christine Bruckner

We just released an updated version of the plugin that supports the use of available dictionaries in your account:

https://appstore.sdl.com/language/app/sdl-machine-translation-cloud/941/

These are not Language Cloud Dictionaries, these are the dictionaries you can load to your SDL Machine Translation Cloud account and they are used server side to present you with the adapted NMT results.

Christine Bruckner said:

I hope that the terminology option of NMT is more refined - tackling the terminology challenge in NMT is not easy, but SDL seems to have done some in-depth research.

I'm not sure this solution offers anything more sophisticated yet.  While we were developing the solution in the plugin I asked a similar question and this was the response:

The first phase of the dictionary matching is done when we detect the matches for each segment and generate the dictionary constraints for the decoder to use. I.e. when processing each segment, we check if there are any dictionary matches for it, and assuming there are, we generate the matched dictionary constraints that define what sections of the segment to replace with what dictionary text. For BCM (Bilingual Content Model) input, it’s a straightforward process since this information is represented in the document and no searching is needed besides converting it to the expected dictionary constraints format used internally by the decoder. In the next phase, the decoder then processes the segment taking the constraints into account.

So they take a dictionary with 1:2:1 mappings source to target (no synonyms).  So good maintenance on the "termbase" is essential to ensure good results.