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In this work, the RWTH automatic speech recognition systems developed for the second TC-STAR evaluation campaign 2006 are presented. The systems were designed to transcribe parliamentary speeches taken from the European Parliament Plenary Sessions (EPPS) in European English and Spanish, as well as speeches from the Spanish Parliament. The RWTH systems apply a two pass search strategy with a fourgram one-pass decoder including a fast vocal tract length normalization variant as first pass. The systems further include several adaptation and normalization methods, minimum classification error trained models, and bayes risk minimization. For all relevant individual components contrastive results are presented on the EPPS Spanish and English data.