Research in techniques to simulate users has a long history within the fields of language processing, speech technologies and conversational interfaces. In this paper, we describe a technique to develop heterogeneous user models that are able to interact with this kind of interfaces. By means of simulated users, it is possible not only to automatically evaluate the overall operation of a conversational interface, but also to assess the impact of the user responses on the decisions that are selected by the system. The selection of the user responses by the simulated user are based on a statistical model that considers the complete history of the interaction to carry out this selection. We describe this technique and its practical application to measure the influence of the most important user's features characteristics that affect the interaction of the simulated user with the a conversational interface.
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