95 research outputs found
Words In Action: Interdisciplinary Approaches To Understanding Word Processing And Storage
Almost all levels of language knowledge and processing (from phonology, to syntax and semantics) are known to be affected by knowledge of word structure at varying degrees. A better understanding of the human strategies involved in learning and processing word structure thus lies at the heart of our comprehension of the basic mechanisms serving both language and cognition and is key to addressing some fundamental challenges for the study of the physiology of grammar. On the 12th and 13th of October 2009, in the Research Area of the Italian National Research Council (CNR) in Pisa, 26 scholars from Europe, Canada and the United States were convened to take part in the European Science Foundation Exploratory Workshop "Words in Action: Interdisciplinary Approaches To Understanding Word Processing And Storage". The workshop brought together experts of various scientific domains and different theoretical inclinations to advance the current awareness of theoretical, historical, psycholinguistic, computational and neurophysiological issues in morphological processing and learning, with a view to assessing levels of research convergence and exploring the potential for synergy and strategic co-operation
Processi cognitivi nell'analisi delle classi verbali dell'italiano: un approccio sperimentale
International audienceL'analisi della flessione, soprattutto verbale, nelle lingue romanze ha ricevuto un notevole impulso negli ultimi anni, in particolare dall'apporto alla ricerca in linguistica teorica di discipline come la psicolinguistica o le scienze cognitive. In questo articolo intendiamo riesaminare la ripartizione dei verbi italiani in classi, e osservare come la teoria morfologica e l'analisi sperimentale possano dare risultati convergenti e contribuire a mettere in luce i processi mentali che costituiscono la base della competenza morfologica dei parlanti (cf. Pirrelli 2007a; 2007b e, per un'illustrazione, Bonami et al. 2008). Nella prima parte, proporremo uno stato dell'arte della ricerca in morfologia flessiva, in particolare nell'ambito del modello "Parole e paradigmi", e suggeriremo una proposta di modellazione del sistema verbale dell'italiano. In particolar modo, ci soffermeremo sul concetto di regolarità, ossia sui criteri che servono a classificare i verbi, e in generale i lessemi, in regolari e irregolari. Nella seconda parte, renderemo conto dei risultati di una ricerca psicolinguistica, i cui risultati confermano, in maniera abbastanza prevedibile, l'esistenza di una macroclasse in italiano (quella dei verbi in -are). Per le altre classi, invece, la situazione è più complessa: anche i modelli di coniugazione generalmente considerati non regolari o semiregolari (ad esempio i verbi ad infinito in -ere atono) costituiscono poli di attrazione importanti nell'organizzazione delle forme flesse dell'italiano e sono facilmente estesi da parte dei locutori
Lexical emergentism and the "frequency-by-regularity" interaction
In spite of considerable converging evidence of the role of inflectional paradigms in word acquisition and processing, little efforts have been put so far into providing detailed, algorithmic models of the interaction between lexical token frequency, paradigm frequency, paradigm regularity. We propose a neurocomputational account of this interaction, and discuss some theoretical implications of preliminary experimental results
T2HSOM: Understanding the Lexicon by Simulating Memory Processes for Serial Order
Over the last several years, both theoretical and empirical approaches to lexical knowledge and encoding have prompted a radical reappraisal of the traditional dichotomy between lexicon and grammar. The lexicon is not simply a large waste basket of exceptions and sub-regularities, but a dynamic, possibly redundant repository of linguistic knowledge whose principles of relational organization are the driving force of productive generalizations. In this paper, we overview a few models of dynamic lexical organization based on neural network architectures that are purported to meet this challenging view. In particular, we illustrate a novel family of Kohonen self-organizing maps (T2HSOMs) that have the potential of simulating competitive storage of symbolic time series while exhibiting interesting properties of morphological organization and generalization. The model, tested on training samples of as morphologically diverse languages as Italian, German and Arabic, shows sensitivity to manifold types of morphological structure and can be used to bootstrap morphological knowledge in an unsupervised way
Validation of Coding Schemes and Coding Workbench
This report presents methodology and results of the validation of the MATE best practice coding schemes and the MATE workbench. The validation phase covered the period from September 1999 to February 2000, and involved project partners as well as Advisory Panel members who kindly volunteered to act as external evaluators. The first part of the report focuses on the evaluation of the theoretical work in MATE while the second part concentrates on the workbench . In both cases, a questionnaire has been used as a core tool to obtain feedback from evaluators. A major probem has been the short time available for evaluation which has implied that less feedbach than originally expected could be obtained . Evaluation of MATE results will continue after the end of the project
Unsupervised Acquisition of Verb Subcategorization Frames from Shallow-Parsed Corpora
In this paper, we reported experiments of unsupervised automatic acquisition of Italian and English verb subcategorization frames (SCFs) from general and domain corpora. The proposed technique operates on syntactically shallow-parsed corpora on the basis of a limited number of search heuristics not relying on any previous lexico-syntactic knowledge about SCFs. Although preliminary, reported results are in line with state-of-the-art lexical acquisition systems. The issue of whether verbs sharing similar SCFs distributions happen to share similar semantic properties as well was also explored by clustering verbs that share frames with the same distribution using the Minimum Description Length Principle (MDL). First experiments in this direction were carried out on Italian verbs with encouraging results
Ontology learning from Italian legal texts
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies
Evaluating Hebbian Self-Organizing Memories for Lexical Representation and Access
The lexicon is the store of words in long-term memory. Any attempt at modelling lexical competence must take issues of string storage seriously. In the present contribution, we discuss a few desiderata that any biologically-inspired computational model of the mental lexicon has to meet, and detail a multi-task evaluation protocol for their assessment. The proposed protocol is applied to a novel computational architecture for lexical storage and acquisition, the "Topological Temporal Hebbian SOMs" (T2HSOMs), which are grids of topologically organised memory nodes with dedicated sensitivity to time-bound sequences of letters. These maps can provide a rigorous and testable conceptual framework within which to provide a comprehensive, multi-task protocol for testing the performance of Hebbian self-organising memories, and a comprehensive picture of the complex dynamics between lexical processing and the acquisition of morphological structure
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