Forspoken definition9/13/2023 ![]() results and NAM’s predictions appears to lie in the lexicality of the stimulus under scrutiny. The key to the discrepancy between the Vitevitch et al. (1997)-who found that high probability nonwords were responded to more, rather than less, quickly-contradict the predictions of NAM. However, the results obtained by Vitevitch et al. ![]() Given the correlation between neighborhood density and segment frequency, NAM predicts that the competition among the words activated in memory should result in nonwords with high phonotactic probability being repeated more slowly than nonwords with low probability. In auditory naming and lexical decision tasks, words with low-density neighborhoods are responded to more quickly than words with high-density neighborhoods.ĭespite the previous success of NAM in predicting recognition speed and accuracy for real words, the model makes an erroneous prediction regarding the effects of phonotactic probability on the processing of nonsense words. For example, in perceptual identification tasks, words with low-density neighborhoods are identified in noise more accurately than words with high-density neighborhoods. Numerous studies ( Cluff & Luce, 1990 Goldinger, Luce, & Pisoni, 1989 Luce, Goldinger, Auer, & Vitevitch, in press Luce & Pisoni, 1998) have confirmed the predictions of NAM. Stated in terms of probabilistic phonotactics, the model predicts that words that share fewer segments and sequences of segments will be responded to more quickly than words that share many segments and sequences of segments. ![]() Thus, NAM predicts that words in high-density phonological neighborhoods will be responded to less quickly and accurately than words occurring in low-density neighborhoods. According to NAM, greater lexical competition results in slower and less accurate processing. Stimulus input (i.e., a spoken word) activates a set or neighborhood of similar sounding words in memory, which then compete for recognition. ![]() According to NAM, spoken words are recognized in the context of phonologically similar words activated in memory. Work by Luce and Pisoni (1998) on the neighborhood activation model (NAM) has demonstrated that neighborhood density affects the speed and accuracy of spoken word recognition. In short, there is a positive correlation between phonotactic probability and neighborhood density. Conversely, low probability phonotactic patterns typically occur in sparse phonological neighborhoods. That is, high probability phonotactic patterns typically occur in dense phonological neighborhoods. A word (or nonword) containing frequently occurring segments and sequences is often phonologically similar to many other words. These results suggest that probabilistic phonotactic information is not only represented in memory, but that it influences the processing of spoken stimuli.Ĭommon segments and sequences found in spoken words with high phonotactic probabilities are, by definition, those segments and sequences found in many words. High probability nonwords were rated more word-like (see also Eukel, 1980) and were repeated faster than low probability nonwords. ![]() (1997) found that subjective ratings as well as response times in an auditory naming task coincide with the objective measures of phonotactic probability. Recent work ( Vitevitch et al., 1997 Vitevitch & Luce, 1998 1999) has shown that probabilistic phonotactic information has demonstrable effects on spoken word recognition. Probabilistic phonotactics refers to the frequency that a particular segment or sequence of segments will occur in a given position in a word or syllable ( Treiman, Kessler, Knewasser, Tincoff, & Bowman, 1996 Vitevitch, Luce, Charles-Luce, & Kemmerer, 1997). ![]()
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