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Two opposing viewpoints have been advanced to account for morphological productivity, one according to which some knowledge is couched in the form of operations over variables, and another in which morphological generalization is primarily determined by similarity. We investigated this controversy by examining the generalization of Portuguese verb stems, which fall into one of three conjugation classes. In Study 1, an elicited production task revealed that the generalization of 2nd and 3rd conjugation stems is influenced by the degree of phonological similarity between novel roots and existing verbs, whereas the 1st conjugation generalizes beyond similarity. In Study 2, we directly contrasted two distinct computational implementations of conjugation class assignment in how well they matched the human data: a similarity-driven model that captures phonological similarities, and a dual-mechanism model that implements an explicit distinction between context-free and similarity-based generalizations. The similarity-driven model consistently underestimated 1st conjugation responses and overestimated proportions of 2nd and 3rd conjugation responses, especially for novel verbs that are highly similar to existing verbs of those classes. In contrast, the expected proportions produced by the dual-mechanism model were statistically indistinguishable from human responses. We conclude that both context-free and context-sensitive processes determine the generalization of conjugations in Portuguese, and that similarity-based algorithms of morphological acquisition are insufficient to exhibit default-like generalization. (C) 2014 Elsevier Inc. All rights reserved.
We offer a dynamical model of phonological planning that provides a formal instantiation of how the speech production and perception systems interact during online processing. The model is developed on the basis of evidence from an experimental task that requires concurrent use of both systems, the so-called response-distractor task in which speakers hear distractor syllables while they are preparing to produce required responses. The model formalizes how ongoing response planning is affected by perception and accounts for a range of results reported across previous studies. It does so by explicitly addressing the setting of parameter values in representations. The key unit of the model is that of the dynamic field, a distribution of activation over the range of values associated with each representational parameter. The setting of parameter values takes place by the attainment of a stable distribution of activation over the entire field, stable in the sense that it persists even after the response cue in the above experiments has been removed. This and other properties of representations that have been taken as axiomatic in previous work are derived by the dynamics of the proposed model. (C) 2016 Elsevier Inc. All rights reserved.
We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better accounted for by an encoding-based model of agreement attraction, compared to a retrieval-based model. A novel methodological contribution of our study is the use of comprehension questions with open-ended responses, so that both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model.
We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT-R based Lewis and Vasishth (2005) model is used to implement these three proposals. Slowed processing is implemented as slowed execution time of parse steps; intermittent deficiency as increased random noise in activation of elements in memory; and resource reduction as reduced spreading activation. As data, we considered subject vs. object relative sentences, presented in a self-paced listening modality to 56 individuals with aphasia (IWA) and 46 matched controls. The participants heard the sentences and carried out a picture verification task to decide on an interpretation of the sentence. These response accuracies are used to identify the best parameters (for each participant) that correspond to the three hypotheses mentioned above. We show that controls have more tightly clustered (less variable) parameter values than IWA; specifically, compared to controls, among IWA there are more individuals with slow parsing times, high noise, and low spreading activation. We find that (a) individual IWA show differential amounts of deficit along the three dimensions of slowed processing, intermittent deficiency, and resource reduction, (b) overall, there is evidence for all three sources of deficit playing a role, and (c) IWA have a more variable range of parameter values than controls. An important implication is that it may be meaningless to talk about sources of deficit with respect to an abstract verage IWA; the focus should be on the individual's differential degrees of deficit along different dimensions, and on understanding the causes of variability in deficit between participants.