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Cross-Linguistic Cognitive Modeling of Verbal Morphology Acquisition

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Abstract

How children acquire and process inflectional morphology is still an open question. Despite the fact that English past tense acquisition has been studied and modeled in depth, the current approaches do not account for many of the errors made by humans. Moreover, not much work has been done with highly inflected languages, like Spanish. However, the modeling of any linguistic phenomenon in different languages is very important in order to understand the general cognitive processes underlying each particular phenomenon. This paper presents an ACT-R dual-mechanism model that accomplishes the task of acquiring verbal morphology systems from one of the simplest systems (the English one) to one of the most complex systems (the Spanish one), by using a double analogy process of stem and suffix. The model proposed was able to match all types of errors that developing children make (from a sample of them), both in English and Spanish. The models for both languages used very similar parameters. The introduced approach not only shows how children could acquire a highly inflected morphology system in terms of dual-mechanism theories but, given its cross-linguistic character, also sheds light on the possible general processes involved in the acquisition and processing of inflectional morphology.

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Notes

  1. Accessible at http://crl.ucsd.edu/experiments/svi/

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Acknowledgments

The authors would like to thank Prof. Harald Clahsen for making available the full contents of their study with Spanish children [14]. We also want to thank Prof. Fraibet Aveledo for making available its unpublished Master’s thesis, related to the same study. This study was supported by projects NEUROMOD (DPI2015-68664-C4-1-R), NETMD (RTC-2015-3967-1) and Intramurales Especiales 2016 (201650E055).

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Correspondence to J. Ignacio Serrano.

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The authors declare that the paper is in compliance with the Ethical Standard of Cognitive Computation journal following COPE (Committee on Publication Ethics) guidelines.

No data from human beings were collected for this study. All data used in this study were collected by a third party and were publicly available under proper license.

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The authors declare that they have no conflict of interest.

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No specific funding was devoted to this study.

Appendix A: ACT-R Parameters

Appendix A: ACT-R Parameters

The proposed model is implemented under ACT-R 6.0 version. Table 10 show the values of the parameters used in the simulations with English and Spanish presented in this paper. Spreading activation, base level learning, optimized learning, and procedural learning are switched on. Partial matching is activated and the penalty values established for each chunk slots are the following. If the INFIN slot is different, a penalty of 5.0 is given (which is practically the same as not allowing the retrieval of a form of a different verb). However, the rest of slots have lower penalties. The MTA slot has a penalty of 1.5, the NP slot a penalty of 0.3, and the CONJ slot a penalty of 0.3. These values are based on previous studies on the acquisition of tense, number, and other grammatical features in Spanish [52, 53].

Table 10 Parameters used in the model for English and Spanish simulations

One of the main criticisms to ACT-R models is the flexibility they present given the wide range of free parameters (combinatorial complexity). However, in the proposed model, all the parameters are set to commonly used values that do not exceed the typical ranges at all, thus supporting the psychological plausibility of the model. The parameter setting was done by comparison with many other models of very different tasks. Wong et al. [51] proposed a database that collects the parameter values of a representative range of published ACT-R models. That database was used to set the parameter values close to the average values of all those studies. Different possible combinations of parameters were tested in the range given by the average and standard deviations, and the one that fits better both the developmental curve and the overall percentages of correct regular and irregular forms was chosen. This way, it is demonstrated that language acquisition can be accomplished using the same general cognitive constraints. Moreover, both the Spanish and the English models work with very similar parameters. Thus, the proposed model does not assume special cognitive abilities for children talking one or the other language (it would be certainly implausible to suppose for example that English children have a much greater capacity to retrieve verb forms from memory). The only parameter that significantly differs from the average value in the study of Wong et al. [51] is the α parameter. The proposed model uses a value much lower than the one used in other cognitive tasks. The reason is that most of the models in the study of Wong et al. [51] try to model the behavior of adults in time-limited tasks. However, the proposed model represents a typical children brain through the long-lasting task of acquiring inflections.

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Oliva, J., Serrano, J.I., del Castillo, M.D. et al. Cross-Linguistic Cognitive Modeling of Verbal Morphology Acquisition. Cogn Comput 9, 237–258 (2017). https://doi.org/10.1007/s12559-017-9454-8

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