In this paper we present a method for defining the question set for the induction of acoustic phonetic decision trees. The method is data driven resulting in a continuous feature space in contrast to the usual categorical one. We apply the features to a multi-lingual speech recognition task, outperforming consistently the standard method using IPA-based characteristics. An extension to cross-lingual applications together with first preliminary results are given too.