Testing between the TRACE model and the fuzzy logical model of speech perception

The TRACE model of speech perception (McClelland & Elman, 1986) is contrasted with a fuzzy logical model of perception (FLMP) (Oden & Massaro, 1978). The central question is how the models account for the influence of multiple sources of information on perceptual judgment. Although the two models can make somewhat similar predictions, the assumptions underlying the models are fundamentally different. The TRACE model is built around the concept of interactive activation, whereas the FLMP is structured in terms of the integration of independent sources of information. The models are tested against test results of an experiment involving the independent manipulation of bottom-up and top-down sources of information. Using a signal detection framework, sensitivity and bias measures of performance can be computed. The TRACE model predicts that top-down influences from the word level influence sensitivity at the phoneme level, whereas the FLMP does not. The empirical results of a study involving the influence of phonological context and segmental information on the perceptual recognition of a speech segment are best described without any assumed changes in sensitivity. To date, not only is a mechanism of interactive activation not necessary to describe speech perception, it is shown to be wrong when instantiated in the TRACE model.     

Attention and perception: An information-integration perspective

Attentional effects in perceptual processing are analyzed within a framework of a fuzzy logical model of perception. The recognition of a pattern is conceptualized as involving three stages of processing: featural evaluation, integration of features, and pattern classification. The model predicts no loss of resolution when multiple sources of information are integrated to recognize a perceptual event. This model is contrasted with a single-channel model in which only one source of information can be recognized at a time. The task involves a relatively novel situation of speech perception by ear and eye. No attentional decrement is observed when observers process both auditory and visual speech specifying a single speech event. This result contrasts with previous studies showing a loss when attention has to be divided between different events along auditory and visual modalities. The different results are interpreted in terms of the number of events that have to be processed. Processing two different modalities leads to an attentional decrement when the two inputs specify different events whereas no attentional decrement occurs when these inputs are integrated to recognize a single event. A distinction is made between detection that requires only the evaluation of a single source of information and recognition that requires the evaluation and integration of multiple sources of information. The current framework is also used to discuss previous empirical and theoretical work and the issue of early versus late selection.     

A pattern recognition account of decision making

In the domain of pattern recognition, experiments have shown that perceivers integrate multiple sources of information in an optimal manner. In contrast, other research has been interpreted to mean that decision making is nonoptimal. As an example, Tversky and Kahneman (1983) have shown that subjects commit a conjunction fallacy because they judge it more likely that a fictitious person named Linda is a bank teller and a feminist than just a bank teller. This judgment supposedly violates probability theory, because the probability of two events can never be greater than the probability of either event alone. The present research tests the hypothesis that subjects interpret this judgment task as a pattern recognition task. If this hypothesis is correct, subjects’ judgments should be described accurately by the fuzzy logical model of perception (FLMP)—a successful model of pattern recognition. In the first experiment, the Linda task was extended to an expanded factorial design with five vocations and five avocations. The probability ratings were described well by the FLMP and described poorly by a simple probability model. The second experiment included (1) two fictitious people, Linda and Joan, as response alternatives and (2) both ratings and categorization judgments. Although the ratings were accurately described by both the FLMP and an averaging of the sources of information, the categorization judgments were described better by the FLMP. These results reveal important similarities in recognizing patterns and in decision making. Given that the FLMP is an optimal method for combining multiple sources of information, the probability judgments appear to be optimal in the same manner as pattern-recognition judgments.