The main focus of this paper is to investigate how aspects of morphologicalregularity may have an impact on early stages of word processing,prior to full lexical access. Here I explore the interaction of regularity andmorphological structure by using a computational simulation of the processof learning Russian verb forms, without any morpho-syntactic or morphosemanticadditional information. With a recurrent variant of self-organisingmemories, namely a Temporal Self-Organising Map, or TSOM, experimentalresults allow an investigation of the impact of incremental learning and onlineprocessing principles on paradigm organisation, by assessing the differentialimpact of several aspects of regularity, ranging from formal transparency andpredictability to allomorphy, on the processing/learning behaviour in a connectionistframework. The proposed analysis suggests a performance-orientedaccount of inflectional regularity in morphology, whereby perception of morphologicalstructure is not the by-product of the design of the human wordprocessor, with rules separated from exceptions, but rather an emergent propertyof the dynamic self-organisation of stored lexical representations, dependenton the adaptive processing history of inflected word forms, intrinsicallygraded and probabilistic.

Modelling the interaction of regularity and morphological structure: the case of Russian verb inflection

Marzi C
Primo
2020

Abstract

The main focus of this paper is to investigate how aspects of morphologicalregularity may have an impact on early stages of word processing,prior to full lexical access. Here I explore the interaction of regularity andmorphological structure by using a computational simulation of the processof learning Russian verb forms, without any morpho-syntactic or morphosemanticadditional information. With a recurrent variant of self-organisingmemories, namely a Temporal Self-Organising Map, or TSOM, experimentalresults allow an investigation of the impact of incremental learning and onlineprocessing principles on paradigm organisation, by assessing the differentialimpact of several aspects of regularity, ranging from formal transparency andpredictability to allomorphy, on the processing/learning behaviour in a connectionistframework. The proposed analysis suggests a performance-orientedaccount of inflectional regularity in morphology, whereby perception of morphologicalstructure is not the by-product of the design of the human wordprocessor, with rules separated from exceptions, but rather an emergent propertyof the dynamic self-organisation of stored lexical representations, dependenton the adaptive processing history of inflected word forms, intrinsicallygraded and probabilistic.
2020
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
morphological complexity
discriminative learning
recurrent neural networks
self-organisation
Russian verb inflection
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Descrizione: Modelling the interaction of regularity and morphological structure: the case 0f Russian verb inflection
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/407424
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