The advent of connectionism in the 80's popularised the idea that the lexical processor consists of a network of parallel processing units selectively firing in response to sensory stimuli. In the light of these assumptions, the most important contribution of connectionism to the theoretical debate on lexical modelling at the time was the utter rejection of the widely accepted idea that word recognition and production require a dichotomous choice between storage and processing. However, in spite of the prima facie psycho-computational allure of this view of the lexicon, early connectionist models also embraced a number of unsatisfactory assumptions about word learning and processing. More recently, a growing number of approaches to inflection in both Psycholinguistics and Theoretical Linguistics developed the view that surface word relations represent a fundamental domain of morphological competence. Learning the morphology of a language amounts to acquiring relations between fully stored lexical forms, which are concurrently available in the speaker's mental lexicon and jointly facilitate processing of morphologically related forms through patterns of emergent self-organisation. This novel view presupposes an integrative language architecture, where storage and processing, far from being conceived of as insulated and poorly interacting modules, are the short-term and the long-term dynamics of the same underlying process of adaptive specialisation of synaptic connections. This view, upheld by recent evidence of the neuro-anatomical bases of short-term and long-term memory processes, crucially hinges on Hebbian principles of synaptic plasticity, which are, in turn, in keeping with mathematical models of discriminative learning. I contend that integrative computer models of Hebbian language learning represent an exciting way forward in current neuro-computational research on word processing, and a persistently fertile legacy of the connectionist revolution.

Storage vs. Processing in Models of Word Inflection. A Neuro-computational Hebbian Perspective

Pirrelli;Vito
2017

Abstract

The advent of connectionism in the 80's popularised the idea that the lexical processor consists of a network of parallel processing units selectively firing in response to sensory stimuli. In the light of these assumptions, the most important contribution of connectionism to the theoretical debate on lexical modelling at the time was the utter rejection of the widely accepted idea that word recognition and production require a dichotomous choice between storage and processing. However, in spite of the prima facie psycho-computational allure of this view of the lexicon, early connectionist models also embraced a number of unsatisfactory assumptions about word learning and processing. More recently, a growing number of approaches to inflection in both Psycholinguistics and Theoretical Linguistics developed the view that surface word relations represent a fundamental domain of morphological competence. Learning the morphology of a language amounts to acquiring relations between fully stored lexical forms, which are concurrently available in the speaker's mental lexicon and jointly facilitate processing of morphologically related forms through patterns of emergent self-organisation. This novel view presupposes an integrative language architecture, where storage and processing, far from being conceived of as insulated and poorly interacting modules, are the short-term and the long-term dynamics of the same underlying process of adaptive specialisation of synaptic connections. This view, upheld by recent evidence of the neuro-anatomical bases of short-term and long-term memory processes, crucially hinges on Hebbian principles of synaptic plasticity, which are, in turn, in keeping with mathematical models of discriminative learning. I contend that integrative computer models of Hebbian language learning represent an exciting way forward in current neuro-computational research on word processing, and a persistently fertile legacy of the connectionist revolution.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC -
dc.authority.people Pirrelli it
dc.authority.people Vito it
dc.collection.id.s 69aaa6b3-f0f0-47c1-b9a1-040bae867ec3 *
dc.collection.name 04.02 Abstract in Atti di convegno *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/19 09:23:50 -
dc.date.available 2024/02/19 09:23:50 -
dc.date.issued 2017 -
dc.description.abstract The advent of connectionism in the 80's popularised the idea that the lexical processor consists of a network of parallel processing units selectively firing in response to sensory stimuli. In the light of these assumptions, the most important contribution of connectionism to the theoretical debate on lexical modelling at the time was the utter rejection of the widely accepted idea that word recognition and production require a dichotomous choice between storage and processing. However, in spite of the prima facie psycho-computational allure of this view of the lexicon, early connectionist models also embraced a number of unsatisfactory assumptions about word learning and processing. More recently, a growing number of approaches to inflection in both Psycholinguistics and Theoretical Linguistics developed the view that surface word relations represent a fundamental domain of morphological competence. Learning the morphology of a language amounts to acquiring relations between fully stored lexical forms, which are concurrently available in the speaker's mental lexicon and jointly facilitate processing of morphologically related forms through patterns of emergent self-organisation. This novel view presupposes an integrative language architecture, where storage and processing, far from being conceived of as insulated and poorly interacting modules, are the short-term and the long-term dynamics of the same underlying process of adaptive specialisation of synaptic connections. This view, upheld by recent evidence of the neuro-anatomical bases of short-term and long-term memory processes, crucially hinges on Hebbian principles of synaptic plasticity, which are, in turn, in keeping with mathematical models of discriminative learning. I contend that integrative computer models of Hebbian language learning represent an exciting way forward in current neuro-computational research on word processing, and a persistently fertile legacy of the connectionist revolution. -
dc.description.affiliations ILC-CNR -
dc.description.allpeople Pirrelli; Vito -
dc.description.allpeopleoriginal Pirrelli, Vito -
dc.description.fulltext none en
dc.description.numberofauthors 1 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/327041 -
dc.identifier.url https://indico.sissa.it/event/12/abstract-book.pdf -
dc.language.iso eng -
dc.relation.conferencedate 22-24/06/2017 -
dc.relation.conferencename International Morphological Processing Conference (MoProc) -
dc.relation.conferenceplace Trieste -
dc.relation.firstpage 19 -
dc.relation.lastpage 19 -
dc.relation.numberofpages 1 -
dc.subject.keywords Hebbian Learning -
dc.subject.keywords Recurrent Neural Networks -
dc.subject.keywords Word Inflection -
dc.subject.singlekeyword Hebbian Learning *
dc.subject.singlekeyword Recurrent Neural Networks *
dc.subject.singlekeyword Word Inflection *
dc.title Storage vs. Processing in Models of Word Inflection. A Neuro-computational Hebbian Perspective en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.02 Abstract in Atti di convegno it
dc.type.miur 274 -
dc.type.referee Sì, ma tipo non specificato -
dc.ugov.descaux1 381136 -
iris.orcid.lastModifiedDate 2024/03/01 16:58:36 *
iris.orcid.lastModifiedMillisecond 1709308716994 *
iris.sitodocente.maxattempts 1 -
Appare nelle tipologie: 04.02 Abstract in Atti di convegno
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