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A Comparison of Four Feature Systems Using Data from Three Psychophysical Methods

Gordon M. Becker
University of Nebraska at Omaha, Omaha, Nebraska

Four feature systems (Miller-Nicely, Singh-Black, Wickelgren, and Chomsky-Halle) were compared under three different perceptual tasks involving the ability of subjects to auditorily discriminate pairs and triads of 22 prevocalic English consonants. More than 1000 listeners participated in these experiments. The features in each system were weighted using multiple regression techniques. The weights differed from one data collection method to another for the same feature system, and from one system to another for the same data collection method. The 11-feature Chomsky-Halle system showed the highest multiple correlation for two of the three data collection methods. However, when weights obtained from one method were used to predict the data from another method, the Chomsky-Halle system was best on only one of the three sets of data. The results raised some questions regarding the generality of the systems, the appropriateness of the features, or the appropriateness of the analysis technique.