Abstract
An experimenter who performs a multidimensional analysis of speech perception data must deal with two problems: (1) differences among subjects in the data and (2) rotation of axes in the solution. The rotational problem is crucial when one seeks to determine whether the “true” perceptual dimensions correspond to a particular set of acoustic measures or articulatory features of the stimuli. A new multidimensional scaling technique devised by Carroll and Chang [Psychometrika, (1970) (to be published)] offers a solution to the rotational problem arrived at by capitalizing on individual differences: the axes derived are those that best account for variations among individuals in terms of a differential weighting model. This paper illustrates the promise this method holds for speech perception studies by an example: data on dissimilarities among nine Swedish vowels published by Hanson [Ericsson Technics 23, 3–175 (1967)] are re-analyzed. Whereas the stimulus set represented three distinctive features, the published solution recovered only two. The Carroll-Chang solution is interpretable in terms of all three features and formant frequencies as well. Additional procedures show that the two solutions differ chiefly in rotation and illustrate how other (superficially rational) rotational criteria can lead to less informative solutions.
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