Cross-modality matching of brightness and loudness.
Author(s) -
Julie Stevens,
Lawrence E. Marks
Publication year - 1965
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.54.2.407
Subject(s) - modality (human–computer interaction) , medical diagnosis , matching (statistics) , computer science , loudness , artificial intelligence , medicine , statistics , mathematics , computer vision , radiology
Proceeding similarly with the data of the remaining subjects, one obtains estimates of 0k2 equal to zero for four of the eight cases; in only one case does dk prove greater than half the value of d. For the whole sample, the average of the oak estimates is less than 2 elements, whereas the average of the d estimates is approximately 7. No sweeping conclusions should be drawn from this result, since the assignments of pairs of redundant critical elements to positions in the display matrices were not entirely random. (The four corner positions were not used and one member of each pair of redundant elements was required to be on an edge of the matrix; these restrictions are eliminated in a study now in progress.) However, it seems likely, in the light of these preliminary data, that the assumption of a geometric distribution of perceptual spans embodied in a serial processing model for visual detection2 will have to be modified. Finally, it might be noted that the technique presented here offers possibilities of comparing perceptual spans for human and infrahuman subjects. It is well known that many animals, notably pigeons and monkeys, can be trained to attend to a viewing screen upon presentation of a signal and can learn discriminations involving symbols such as those used as critical elements in experiments on visual detection. By training animals to discriminate between displays including varying numbers of redundant critical elements per display, one can estimate statistics of the distribution of perceptual span, and thus in turn evaluate hypotheses as to how subjects of different species process information from visual displays. * This research was supported in part by grant G-24264 from the National Science Foundation. 1 Swets, J. A., ed., Signal Detection and Recognition by Human Observers (New York: John Wiley and Sons, 1964). 2 Estes, W. K., and H. A. Taylor, "A detection method and probabilistic models for assessing information processing from brief visual displays," these PROCEEDINGS, 52, 446-454 (1964). 3 Estes, W. K., and H. A. Taylor, "Visual detection in relation to display size and redundancy of critical elements," Tech. Rept. No. 68, Stanford Univ., 1965.
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