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In this paper, we describe development and evaluation of handsfree spoken dialogue system which is used for railway station guidance. In the application at the railway station, noise robustness is the most essential issue for the dialogue system. To address the problem, we introduce two key techniques in our proposed hands-free system; (a) blind spatial subtraction array (BSSA) as a preprocessing, which can efficiently reduce nonstationary and diffuse noises in real-time, and (b) robust voice activity detection (VAD) based on speech decoding for further improvement of speech recognition accuracy. The experimental assessment of the proposed dialogue system reveals that the combination of real-time BSSA and robust VAD can provide the recognition accuracy of more than 80% under adverse railway-station noise conditions.