Hi,
I found this older tutorial to be very useful as well:
"Practical Domain Adaptation" by Marcello Federico and Nicola Bertoldi
http://www.mt-archive.info/10/AMTA-2012-Bertoldi-ppt.pdf
(The document formatting is unfortunately slightly messed up.)
SMT research survey wiki:
http://www.statmt.or
You could try this tutorial
http://www.statmt.org/mtma15/uploads/mtma15-domain-adaptation.pdf
On 14/08/15 20:20, Vincent Nguyen wrote:
> I had read this section, which deals with translation model combination.
> not much on language model or tuning.
>
> For instance : if I want to make sure that
I had read this section, which deals with translation model combination.
not much on language model or tuning.
For instance : if I want to make sure that a specific expression
"titres" is translated in "equities" from French to English.
These 2 words have specifically to be in the Monolingual
Hi Vincent,
this section describes some domain adaptation methods that are
implemented in Moses: http://www.statmt.org/moses/?n=Advanced.Domain
It is incomplete (focusing on parallel data and the translation model),
and does not recommend best practices.
In general, my recommendation is to use
Hi,
I can't find a sort of "tutorial " on domain adaptation path to follow.
I read this in the doc :
The language model should be trained on a corpus that is suitable to the
domain. If the translation model is trained on a parallel corpus, then
the language model should be trained on the output
Do you mean "sense spotting" as in the 2013 Carpuat et al paper:
http://www.aclweb.org/anthology/P/P13/P13-1141.pdf ?
There is already an implementation here that you can use:
www.github.com/hal3/IntrinsicPSDEvaluation/
~amittai
On 6/27/15 21:25, Marwa Refaie wrote:
>
>
> Hi all ,
> I try to im
Hi all , I try to implement any of the experiments for Domain Adaptation ...
Any recommendation please , or how to experiment sense spotting ?
Marwa N. Refaie
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