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 models 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 _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
