in our case parsing performance is not directly dependent on the WER but rather on the type of errors made.
since the RoboCup corpus is rather small and n-gram models are typically learned from large amounts of data, in addition we interpolated the trigram models trained solely on the in-domain RoboCup corpus each with a large background language model trained on a broadcast news corpus, i.e.