I would start simple, then build it up once i know what it's doing, eg.
start with
input-factors = word stem pos
output-factors = word stem pos
alignment-factors = "word -> word"
translation-factors = "word+stem+pos -> word+stem+pos"
reordering-factors = "word -> word"
generation-factors = ""
decoding-steps = "t0"
Hieu Hoang
http://www.hoang.co.uk/hieu
On 27 July 2016 at 11:46, Gmehlin Floran <[email protected]> wrote:
> Hi,
>
> I am trying to build a factored translation model using stems and
> part-of-speech for a week now and I cannot have satisfying results. This
> probably comes from my factor configuration as I probably do not fully
> understand how it work (I am following the paper Factored Translation Model
> from Koehn and Hoang).
>
> I previously built a standard phrase based model (with the same corpus)
> which gave me around 24-25 BLEU score (DE-EN). For my actual factored
> model, BLEU score is around 1 (?).
>
> I tried opening the moses.ini's, (tuned or not) to see if I could have a
> something translated by copy/pasting some lines from the original corpus,
> but it only translates from german to german and does not recognize most of
> the words if not all.
>
> The motivation behind the factored model is that there are too many OOVs
> with the standard phrase-base, so I wanted to try using stems to reduce
> them.
>
> I am annotating the corpus with TreeTagger and the factor configuration is
> as following :
>
> input-factors = word stem pos
> output-factors = word stem pos
> alignment-factors = "word+stem -> word+stem"
> translation-factors = "stem -> stem,pos -> pos"
> reordering-factors = "word -> word"
> generation-factors = "stem -> pos,stem+pos -> word"
> decoding-steps = "t0,g0,t1,g1"
>
> Is there something wrong with that ?
>
> I only use a single language model over surface forms as the LM over POS
> yields a segmentation fault in the tuning phase.
>
> Does anyone have an idea how I should configure my model to exploit stems
> in the source language ?
>
> Thanks a lot,
>
> Floran
>
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