A dialog switching strategy for information retrieval in noisy environments based on a confidence score.

This paper presents a dialog switching strategy for information retrieval in human-robot dialog in order to cope with different intensities of background noise. The strategy dynamically switches between a more open and a closed dialog scheme based on a continuously adapted confidence score evaluating resulting numbers of cases of recognition and non-recognition of user speech, which are dependent on the level of background noise. Thereby, more natural and more robust dialog components are balanced, respectively. Experimental results are presented, illustrating the effectiveness of the approach.