Thanks Hieu for pointing me to this section of your thesis. This is really useful.
- Sriram On Thu, Apr 18, 2013 at 2:30 PM, Hieu Hoang <[email protected]> wrote: > '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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