Models for estimating the similarity between two utterances are fundamental in speech technology. While fairly good automatic measures exist for semantic similarity, we only recently built a model of pragmatic similarity, the first. We propose to present this model by letting participants try out our Pragmatically Similar Utterance Finder. This system listens to one side of a live conversation, identifies the utterances, and for each retrieves the most similar utterances, according to our model, from a large corpus. Participants and viewers will then be able to hear these utterances, and judge for themselves the prospects for pragmatic-similarity modeling.