text: We compare two language modelling toolkits , the CMU and the SRI toolkit and arrive at three results : 1 -RRB- [[ word-lemma based feature function models ]] produce better results than << token-based models >> , 2 -RRB- adding a PoS-tag feature function to the word-lemma model improves the output and 3 -RRB- weights for lexical translations are suitable if the training material is similar to the texts to be translated .