The goal of this paper is to present a new method to automatically generate pronunciation rules for automatic segmentation of speech - the German MAUSER system. MAUSER is an algorithm which generates pronunciation rules independently of any domain dependent training data either by clustering and statistically weighting self-learned rules according to a small set of phonological rules clustered by categories or by re-weighting "seen"' phonological rules. By this method we are able to automatically segment cost-effectively large corpora of mainly unprompted speech.