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 .