Latest smartphones often have more than one microphone in order to perform noise reduction. Although research on speech enhancement is already exploiting this new feature, robust speech recognition is not still benefiting from it. In this paper we propose two feature enhancement methods especially developed for the case of a smartphone with a dual-microphone operating in an adverse acoustic environment. In order to test these proposals, we have already developed a new experimental framework which includes a noisy speech database (based on AURORA2) which emulates the acquisition of dual-microphone data. Our experimental results show a clear improvement in terms of word accuracy in comparison with both using a power level difference-based speech enhancement algorithm and a single channel feature compensation approach.