How TRACE Works
The TRACE model is a connectionist network with an input layer and three processing layers: pseudo-spectra (feature), phoneme and word. Figure 2 shows a schematic diagram of TRACE. There are three types of connectivity: (1) feedforward excitatory connections from input to features, features to phonemes, and phonemes to words; (2) lateral (i.e., within layer) inhibitory connections at the feature, phoneme and word layers; and (3) top-down feedback excitatory connections from words to phonemes. The input to TRACE works as follows. The user provides a phoneme sequence that is converted into a multi-dimensional feature vector. This is an approximation of acoustic spectra extended in time. The input vector is revealed a little at a time to simulate the temporal nature of speech. As each new chunk of input is presented, this sends activity along the network connections, changing the activation values in the processing layers. Features activate phoneme units, and phonemes activate word units. Parameters govern the strength of the excitatory and inhibitory connections, as well as many other processing details. There is no specific mechanism that determines when a word or a phoneme has been recognized. If simulations are being compared to reaction time data from a perceptual experiment (e.g. lexical decision), then typically an activation threshold is used. This allows for the model behavior to be interpreted as recognition, and a recognition time to be recorded as the number of processing cycles that have elapsed. For deeper understanding of TRACE processing dynamics, readers are referred to the original publication and to a TRACE software tool that runs simulations with a graphical user interface.
Read more about this topic: Trace (psycholinguistics)
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