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In two experiments, we investigate to what extent various visual saliency cues in realistic visual scenes cause speakers to overspecify their definite object descriptions with a redundant color attribute. The results of the first experiment demonstrate that speakers are more likely to redundantly mention color when visual clutter is present in a scene as compared to when this is not the case. In the second experiment, we found that distractor type and distractor color affect redundant color use: Speakers are most likely to overspecify if there is at least one distractor object present that has the same type, but a different color than the target referent. Reliable effects of distractor distance were not found. Taken together, our results suggest that certain visual saliency cues guide speakers in determining which objects in a visual scene are relevant distractors, and which not. We argue that this is problematic for algorithms that aim to generate human-like descriptions of objects (such as the Incremental Algorithm), since these generally select properties that help to distinguish a target from all objects that are present in a scene. [ABSTRACT FROM AUTHOR]

In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order. The authors argue that there are potentially many different Preference Orders that could be considered, while often no evidence is available to determine which is a good one. In this brief note, however, we suggest (based on a learning curve experiment) that finding a Preference Order for a new domain may not be so difficult after all, as long as one has access to a handful of human-produced descriptions collected in a semantically transparent way. We argue that this is due to the fact that it is both more important and less difficult to get a good ordering of the head than of the tail of a Preference Order. [ABSTRACT FROM AUTHOR]