Hi Philipp,

I will look into tree-to-String and String-to-Tree models. However i did
work with relax parses, and used left-binarization and right
binarization on my parsed data before I ran training.
Although it improved scores over the normal tree-to-tree yet its was
still not sufficient to beat the PBSMT. However I am yet to run
experiments with SAMT 1-4.

Thanks and regards,

Pratyush

On 09/04/11 15:53, Philipp Koehn wrote:
> Hi,
>
> the syntax models are still pretty much research-grade and may
> disappoint when using them out of the box.
>
> Especially, tree-to-tree models will lead to much more restricted
> models, with less rules, and rules that are less applicable.
>
> You may see better results by starting with tree-to-string or
> string-to-tree models. You should also look at the parse relaxation
> which is inspired by work by Zollmann&Venugopal and the
> tree binarization work at ISI.
>
> -phi
>
> On Fri, Apr 8, 2011 at 11:27 AM, Pratyush Banerjee
> <[email protected]> wrote:
>   
>> Hi All,
>>
>> We have been trying to use Syntax Models for Moses for some time now.
>> We have trained tree-to-tree models and HPB models and were trying to
>> compare the results with standard PBSMT models.
>>
>> We use en-de as language pairs and about 1.2 million lines as training data.
>> For tree to tree models we have used Berkeley Parser for parsing both
>> languages.
>>
>> However i found that Tree-to-Tree scores were much lower(about 4 BLEU
>> points) compared to the PBSMT models. The HPB model (hierarchical moses
>> without syntax) is slightly better than the PBSMT models.
>>
>> Is this behaviour normal. I am quite new to syntax based models, hence the
>> question.
>>
>> Also do we need to parse the devsets during tuning of the tree-to-tree
>> models ?
>>
>> Thanks and regards,
>>
>> Pratyush Banerjee
>>
>> _______________________________________________
>> Moses-support mailing list
>> [email protected]
>> http://mailman.mit.edu/mailman/listinfo/moses-support
>>
>>
>>     
>   

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