formant frequency detectors, and periodicity detectors. These detectors compute relational attributes of the signal. The next step is an array of phonetic feature detectors. They examine the set of auditory property values over a chunk of time and make decisions as to whether a particular phonetic feature is present (i.e. nasality). All of these decisions are language specific. In conclusion, it should be possible to find a relatively uniform mapping between acoustic patterns and perceived speech, as long as the acoustic patterns are analyzed in appropriate ways (Stevens, 1986).TRACE ModelThe TRACE model consists of a large number of units, broken down into three levels, which are the feature, phoneme, and word levels. Each of these levels contains highly interconnected processing units called nodes. TRACE accounts for several different aspects of human speech perception. Like humans, TRACE uses information from overlapping portions of the speech wave to identify successive phonemes. The model's tendency toward categorical perception is affected by many of the same parameters, which affect the degree of categorical perception shown by humans (Elman and McClelland, 1986). This model is considered a connectionist model, based on neural networks. In the lowest level, the nodes represent the phonetic features. In the second level the nodes represent the phonetic segments. Lastly, the nodes represent the words. When a particular level of activation is reached the nodes are fired, which indicates that a feature, phoneme, or word is present (Moore, 1997).At the feature level, there are banks of detectors for each of the dimensions of speech sounds. Each bank is reproduced for several successive moments in time. At the word level there are detectors for every word. The detectors are replicated across time slices. Units with adjacent centers span overlapping ranges of slices (Elman and McClelland, 1986).When a node fires, activat...
