Actually the approximation I expect to be: p(e|f)=p(f|e)
Why would you expect this to give poor results if the TM is well trained? Surely the results of my filtering experiments provve otherwise. James ________________________________________ From: moses-support-boun...@mit.edu <moses-support-boun...@mit.edu> on behalf of Rico Sennrich <rico.sennr...@gmx.ch> Sent: Wednesday, June 17, 2015 5:32 PM To: moses-support@mit.edu Subject: Re: [Moses-support] Major bug found in Moses Read, James C <jcread@...> writes: > I have been unable to find a logical explanation for this behaviour other than to conclude that there must be some kind of bug in Moses which causes a TM only run of Moses to perform poorly in finding the most likely translations according to the TM when > there are less likely phrase pairs included in the race. I may have overlooked something, but you seem to have removed the language model from your config, and used default weights. your default model will thus (roughly) implement the following model: p(e|f) = p(e|f)*p(f|e) which is obviously wrong, and will give you poor results. This is not a bug in the code, but a poor choice of models and weights. Standard steps in SMT (like tuning the model weights on a development set, and including a language model) will give you the desired results. _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
