We used a standard implementation of IBM Model 4 ( Och and Ney 2003 ) and because changing the existing code is not trivial , we could not use the same stopping criterion to avoid overfitting and we are not able to produce precision/recall curves .
a systematic comparison of various statistical alignment models
Franz Josef Och Hermann Ney
Because our approach is orthogonal to the base model used , the constraints described here could be applied in principle to IBM Model 4 if exact inference was efficient , hopefully yielding similar improvements . We used a standard implementation of IBM Model 4 ( Och and Ney 2003 ) and because changing the existing code is not trivial , we could not use the same stopping criterion to avoid overfitting and we are not able to produce precision/recall curves . We trained IBM Model 4 using the default configuration of the
We used a standard implementation of IBM Model 4 ( @@CITATION ) and because changing the existing code is not trivial , we could not use the same stopping criterion to avoid overfitting and we are not able to produce precision/recall curves .