In this paper, we propose an integrated approach for system combination named Driven Decoding Algorithm (DDA). It consists in guiding the search algorithm of a primary ASR system by the outputs of a auxiliary systems. We first evaluate this method in simple configuration in which the primary search is driven by the one-best hypothesis of a single auxiliary system. Then, we generalize DDA to confusion-network driven decoding and we propose a general combination schemes for multiple system combination. The proposed extended DDA is evaluated using 3 ASR systems from different labs. Results show that generalized-DDA outperforms significantly ROVER method : we obtain a 15.7% relative word error rate improvement with respect to the best single system, as opposed to 8.5% with the ROVER combination.