This paper contains a description of the Philips/RWTH 1998 HUB4 system which has been build in a joint e_ort of Philips Research Laboratories Aachen and Aachen University ofTechnology. We will focus our discussion on recent improvements compared to the original 1997 HUB4 system and evaluate them on the HUB4'97 evaluation data. The paper will deal with 1. a rough system overview including feature extraction, acoustic training, audio stream segmentation, and decoding 2. log-linear interpolation of distance-language models, 3. and the integration of various acoustic and language models via Discriminative Model Combination (DMC). The performance of the described system is 23% (relative) better than the performance of the 1997 Philips HUB4 system. A word error rate of 17.9% was achieved on the 1997 HUB4 evaluation set, compared to 23.5% using the original 1997 system.