Here is the score of Chinese-Arabic
using: mteval-v12.pl
Evaluation of cn-to-ar translation using:
src set "test2010" (1 docs, 1000 segs)
ref set "test2010" (1 refs)
tst set "test2010" (1 systems)
NIST score = 6.3938 BLEU score = 0.4120 for system "chinese-arabic"
From: [email protected]
To: [email protected]
Date: Sat, 25 Sep 2010 02:19:00 +0800
Subject: Re: [Moses-support] wrong alignment
Thank Miles,
language model:
-order 5 -interpolate -kndiscount -unk
PhraseTable training command:
-alignment grow-diag-final
-reordering msd-bidirectional-fe
-mgiza -mgiza-cpus 8
best regards
> From: [email protected]
> Date: Fri, 24 Sep 2010 19:09:50 +0100
> Subject: Re: [Moses-support] wrong alignment
> To: [email protected]
> CC: [email protected]
>
> it is probably more helpful to give the number of sentences you used
> for language model training (and other details, eg ngram order).
>
> but at first glance that looks like a tiny amount of language model
> data --i would expect to see something closer to 2GB or so, depending
> upon representation
>
> Miles
>
> 2010/9/24 musa ghurab <[email protected]>:
> >
> > Thank Burger,
> >
> >
> > here are some informations:
> > Language model: 45MB
> > Phrase Table: 26MB
> > Reordering Model: 36MB
> >
> > but I'm still waiti! ng for tuning to finish
> >
> >
> >
> >> From: [email protected]
> >> To: [email protected]
> >> Date: Fri, 24 Sep 2010 13:40:40 -0400
> >> Subject: Re: [Moses-support] wrong alignment
> >>
> >> musa ghurab wrote:
> >>
> >> > I trained a system of Chinese-Arabic language, but many alignments
> >> > are wrong.
> >> > The same thing to lexical model, where are many words are wrongly
> >> > aligned
> >> > Here is an example of lexical model (lex.e2f):
> >>
> >> The point of Moses is not to get good alignments, but to get good
> >> translation output. The target language model will help the decoder
> >> to pick good translations, even if the translation probabilities that
> >> come out of the alignment do not appear to be ideal. A grea! t deal of
> >> research effort has been wasted (in my opin ion) on getting better
> >> alignments, without actually achieving better translation.
> >>
> >> Have you run the resulting model! s on a test set? What was the score?
> >> How big is your language model? More LM data is probably the easiest
> >> way to make up for what might appear to be poor alignments.
> >>
> >> - John D. Burger
> >> MITRE
> >>
> >> _______________________________________________
> >> Moses-support mailing list
> >> [email protected]
> >> http://mailman.mit.edu/mailman/listinfo/moses-support
> >
> > _______________________________________________
> > Moses-support mailing list
> > [email protected]
> > http://mailman.mit.edu/mailman/listinfo/moses-support
> >
> >
>
>
>
> --
> The University of Edinb! urgh is a charitable body, registered in
> Scotland, with registration number SC005336.
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