Structural Equations in Language Learning
Identifieur interne : 003704 ( Istex/Corpus ); précédent : 003703; suivant : 003705Structural Equations in Language Learning
Auteurs : Michael MoortgatSource :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of type-assignment equations. A hard-wired structural component is problematic if one want to address issues of structural variation. Our starting point is a type-logical architecture with separate modules for the logical and the structural components of the computational system. The logical component expresses invariants of grammatical composition; the structural component captures variation in the realization of the correspondence between form and meaning. Learning in this setting involves finding the solution to both the type-assignment equations and the structural equations of the language at hand. We develop a view on these two subtasks which pictures learning as a process moving through a two-stage cycle. In the first phase of the cycle, type assignments are computed statically from structures. In the second phase, the lexicon is enhanced with facilities for structural reasoning. These make it possible to dynamically relate structures during on-line computation, or to establish off-line lexical generalizations. We report on the initial experiments in [15] to apply this method in the context of the Spoken Dutch Corpus. For the general type-logical background, we refer to [12]; §1 has a brief recap of some keyfeat ures.
Url:
DOI: 10.1007/3-540-48199-0_1
Links to Exploration step
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<front><div type="abstract" xml:lang="en">Abstract: In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of type-assignment equations. A hard-wired structural component is problematic if one want to address issues of structural variation. Our starting point is a type-logical architecture with separate modules for the logical and the structural components of the computational system. The logical component expresses invariants of grammatical composition; the structural component captures variation in the realization of the correspondence between form and meaning. Learning in this setting involves finding the solution to both the type-assignment equations and the structural equations of the language at hand. We develop a view on these two subtasks which pictures learning as a process moving through a two-stage cycle. In the first phase of the cycle, type assignments are computed statically from structures. In the second phase, the lexicon is enhanced with facilities for structural reasoning. These make it possible to dynamically relate structures during on-line computation, or to establish off-line lexical generalizations. We report on the initial experiments in [15] to apply this method in the context of the Spoken Dutch Corpus. For the general type-logical background, we refer to [12]; §1 has a brief recap of some keyfeat ures.</div>
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<mods version="3.6"><titleInfo lang="en"><title>Structural Equations in Language Learning</title>
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<name type="personal"><namePart type="given">Michael</namePart>
<namePart type="family">Moortgat</namePart>
<affiliation>Utrecht Institute of Linguistics — OTS, Trans 10, 3512 JK, Utrecht, The Netherlands</affiliation>
<affiliation>E-mail: Michael.Moortgat@let.uu.nl</affiliation>
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<abstract lang="en">Abstract: In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of type-assignment equations. A hard-wired structural component is problematic if one want to address issues of structural variation. Our starting point is a type-logical architecture with separate modules for the logical and the structural components of the computational system. The logical component expresses invariants of grammatical composition; the structural component captures variation in the realization of the correspondence between form and meaning. Learning in this setting involves finding the solution to both the type-assignment equations and the structural equations of the language at hand. We develop a view on these two subtasks which pictures learning as a process moving through a two-stage cycle. In the first phase of the cycle, type assignments are computed statically from structures. In the second phase, the lexicon is enhanced with facilities for structural reasoning. These make it possible to dynamically relate structures during on-line computation, or to establish off-line lexical generalizations. We report on the initial experiments in [15] to apply this method in the context of the Spoken Dutch Corpus. For the general type-logical background, we refer to [12]; §1 has a brief recap of some keyfeat ures.</abstract>
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<subTitle>4th International Conference, LACL 2001 Le Croisic, France, June 27–29, 2001 Proceedings</subTitle>
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<name type="personal"><namePart type="given">Philippe</namePart>
<namePart type="family">de Groote</namePart>
<affiliation>INRIA Lorraine, 615 rue du Jardin Botanique, B.P. 101, 54602, Villers-lès-Nancy Cedex, France</affiliation>
<affiliation>E-mail: Philippe.deGroote@loria.fr</affiliation>
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<name type="personal"><namePart type="given">Glyn</namePart>
<namePart type="family">Morrill</namePart>
<affiliation>Universitat Politècnica de Catalunya, Jordi Girona Salgado, 1-3, 08028, Barcelona, Spain</affiliation>
<affiliation>E-mail: morrill@lsi.upc.es</affiliation>
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<name type="personal"><namePart type="given">Christian</namePart>
<namePart type="family">Retoré</namePart>
<affiliation>Faculté des Sciences, Institut de recherche en Informatique de Nantes (IRIN), 2, rue de la Houssinière, B.P. 92208, 44322, Nantes Cedex 03, France</affiliation>
<affiliation>E-mail: retore@irisa.fr</affiliation>
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<topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic>
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<identifier type="DOI">10.1007/3-540-48199-0</identifier>
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