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 <mossaghu...@hotmail.com>:
>
> Thank Burger,
>
>
> here are some informations:
> Language model:   45MB
> Phrase Table:      26MB
> Reordering Model: 36MB
>
> but I'm still waiting for tuning to finish
>
>
>
>> From: j...@mitre.org
>> To: moses-support@mit.edu
>> 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 great deal of
>> research effort has been wasted (in my opinion) 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
>>
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>
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>



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