'is good' --> is not good
On 18 April 2013 09:57, Hieu Hoang <[email protected]> wrote: > If you are using multiple phrase-tables and generation tables, I don't > think there's much you can do about the speed of the decoding. Also, the > translation quality is good with this configuration > > You can have a look analysis on page 40 here: > http://statmt.org/~s0565741/download/ddd.pdf > > Instead of > --translation-factors 0-0+1-1 --generation-factors 1-0 --decoding-steps > t0,t1,g0 > you're better off doing > --translation-factors 0,1-0,1 > > > > > On 17 April 2013 17:03, Sriram venkatapathy <[email protected] > > wrote: > >> >> Thanks Philipp. >> >> I had tried with very tight t-table limits, even with a limit of 1 for >> both words and pos tags and still it didn't work for this example sequence. >> This was surprising. >> >> I hope I can avoid shorter phrase-lengths because the task I have in mind >> would require me to have default phrase lengths at least at the POS tag >> level. And, would like to avoid using factored model as backoff too because >> I would like to encourage those translations that have a particular pattern >> of POS tags. >> >> - Sriram >> >> >> On Tue, Apr 16, 2013 at 9:29 PM, Philipp Koehn <[email protected]>wrote: >> >>> Hi, >>> >>> the translation option expansion of factored models may explode in the >>> setup that you use above >>> (there are many possible lemma and pos mappings, and the product of >>> them is explored during >>> your first two decoding steps). >>> >>> You could remedy this by: >>> - use shorter phrase lengths >>> - use tighter t-table limits >>> - use the factored model only as backoff >>> >>> -phi >>> >>> On Mon, Apr 15, 2013 at 4:15 PM, Sriram venkatapathy >>> <[email protected]> wrote: >>> > >>> > The decoder (with a factored model) seems to get stuck for certain >>> > sentences. For example, >>> > >>> > It gets stuck for the sentence : >>> > >>> > saint|noun mary|noun immaculate|adj catholic|nadj church|noun >>> > >>> > While working without any problem for the following sentences : >>> > >>> > saint|noun mary|noun immaculate|adj catholic|noun church|noun >>> > saint|noun mary|noun immaculate|adj large|nadj church|noun >>> > saint|noun mary|noun immaculate|adj large|adj church|noun >>> > >>> > >>> > Here are the training parameters, >>> > --translation-factors 0-0+1-1 --generation-factors 1-0 --decoding-steps >>> > t0,t1,g0 >>> > >>> > Factor 0 in both source and target are words >>> > Factor 1 in both source and target and part-of-speech tags >>> > >>> > Any suggestions about what I should be looking at to identify the >>> problem ? >>> > In the verbose mode, I see that for the problem sentences, the stage of >>> > 'collection of translation options' doesn't finish. >>> > >>> > Thanks ! >>> > - Sriram >>> > >>> > >>> > _______________________________________________ >>> > 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 >> >> > > > -- > Hieu Hoang > Research Associate > University of Edinburgh > http://www.hoang.co.uk/hieu > > -- Hieu Hoang Research Associate University of Edinburgh http://www.hoang.co.uk/hieu
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