Access to meaning from visual input: Object and word frequency effects in categorization behavior.

Object and word recognition are both cognitive processes that transform visual input into meaning. Reading words, the frequency of their occurrence (“word frequency”, WF) strongly modulates recognition performance. Does the frequency of objects in our world also affect their recognition? With object-labels available in real-world image datasets, one can now estimate the frequency of occurrence of objects in scenes ("object frequency", OF). We explored frequency effects in word and object recognition behavior with new OF measures as well as established WF measures. We obtained response times from a natural vs. man-made categorization task (Experiment 1) and a matching-mismatching priming task (Experiment 2), involving paired words and images of object concepts. In Experiment 1, only a WF measure (SUBTLEX, based on subtitles) showed a facilitatory effect (i.e., faster responses to frequent stimuli) for both words and object recognition. In Experiment 2, we replicated SUBTLEX WF effect for both stimulus types, but only when the task included cross-modal priming (i.e., word-to-object or object-to-word) and not during repetition priming. Likewise, only in cross-modal priming, we found an OF effect, but with faster responses for both stimulus types when objects occur less frequently in image databases. This suggests that recognition can be more effective when objects are more rare because the limited experience with them makes their concept more distinct and informative. In sum, both object and word recognition are faster when their concepts are often used in language, but also their distinctiveness seems to modulate the efficiency of access to semantic representations.