OperaV1, PascalFrancis, Corpus, bibRecord, 000130

Towards an exemplar-based model of stress in English noun-noun compounds

Identifieur interne : 000130 ( PascalFrancis/Corpus ); précédent : 000129; suivant : 000131

Towards an exemplar-based model of stress in English noun-noun compounds

Auteurs : Sabine Arndt-Lappe

Source :

Journal of linguistics [ 0022-2267 ] ; 2011.

RBID : Francis:12-0245472

Descripteurs français

Pascal (Inist)
- Accent, Nom composé, Phonologie, Algorithme, Analyse de corpus, Anglais.

English descriptors

KwdEn :
- Algorithm, Compound noun, Corpus analysis, English, Phonology, Stress.

Abstract

It is well known that stress assignment in English noun-noun compounds is non-uniform (compare e.g. left-prominent ópera glasses and right-prominent steel bridge), and recent corpus-based studies (e.g. Plag et al. ₂₀₀₇, ₂₀₀8) have shown that categorical, rule-based approaches that make use of argument structure (e.g. Giegerich ₂₀₀₄) or semantics (e.g. Fudge ₁₉8₄) are not able to account satisfactorily for the existing variability. Using data from the corpus studies by Plag and collegues, I argue in this paper that an exemplar-based approach is better-suited to accounting for stress assignment in English noun-noun compounds than a traditional, rule-based paradigm. Specifically, it is shown that two current implementations of exemplar-based algorithms, TiMBL (Daelemans et al. ₂₀₀₇) and AM::Parallel (Skousen & Stanford 2007), clearly outperform comparable rule models in terms of how well they predict stress assignment in the corpora. Furthermore, systematic testing reveals that the reasons for the differences between exemplar and rule models mainly lie in their ability to incorporate detailed, non-abstract information (specifically, constituent family information). The present study therefore adds to the growing evidence in favour of the importance of constituent family information in compounding (e.g. Gagne 200I, Krott, Schreuder & Baayen 2002).

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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C01	`01`		`ENG`	@0 It is well known that stress assignment in English noun-noun compounds is non-uniform (compare e.g. left-prominent ópera glasses and right-prominent steel bridge), and recent corpus-based studies (e.g. Plag et al. ₂₀₀₇, ₂₀₀8) have shown that categorical, rule-based approaches that make use of argument structure (e.g. Giegerich ₂₀₀₄) or semantics (e.g. Fudge ₁₉8₄) are not able to account satisfactorily for the existing variability. Using data from the corpus studies by Plag and collegues, I argue in this paper that an exemplar-based approach is better-suited to accounting for stress assignment in English noun-noun compounds than a traditional, rule-based paradigm. Specifically, it is shown that two current implementations of exemplar-based algorithms, TiMBL (Daelemans et al. ₂₀₀₇) and AM::Parallel (Skousen & Stanford 2007), clearly outperform comparable rule models in terms of how well they predict stress assignment in the corpora. Furthermore, systematic testing reveals that the reasons for the differences between exemplar and rule models mainly lie in their ability to incorporate detailed, non-abstract information (specifically, constituent family information). The present study therefore adds to the growing evidence in favour of the importance of constituent family information in compounding (e.g. Gagne 200I, Krott, Schreuder & Baayen 2002).
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Format Inist (serveur)

NO :	FRANCIS 12-0245472 INIST
ET :	Towards an exemplar-based model of stress in English noun-noun compounds
AU :	ARNDT-LAPPE (Sabine)
AF :	Universität Siegen/Allemagne (1 aut.)
DT :	Publication en série; Niveau analytique
SO :	Journal of linguistics; ISSN 0022-2267; Royaume-Uni; Da. 2011; Vol. 47; No. 3; Pp. 549-585; Bibl. 1 p.1/2
LA :	Anglais
EA :	It is well known that stress assignment in English noun-noun compounds is non-uniform (compare e.g. left-prominent ópera glasses and right-prominent steel bridge), and recent corpus-based studies (e.g. Plag et al. ₂₀₀₇, ₂₀₀8) have shown that categorical, rule-based approaches that make use of argument structure (e.g. Giegerich ₂₀₀₄) or semantics (e.g. Fudge ₁₉8₄) are not able to account satisfactorily for the existing variability. Using data from the corpus studies by Plag and collegues, I argue in this paper that an exemplar-based approach is better-suited to accounting for stress assignment in English noun-noun compounds than a traditional, rule-based paradigm. Specifically, it is shown that two current implementations of exemplar-based algorithms, TiMBL (Daelemans et al. ₂₀₀₇) and AM::Parallel (Skousen & Stanford 2007), clearly outperform comparable rule models in terms of how well they predict stress assignment in the corpora. Furthermore, systematic testing reveals that the reasons for the differences between exemplar and rule models mainly lie in their ability to incorporate detailed, non-abstract information (specifically, constituent family information). The present study therefore adds to the growing evidence in favour of the importance of constituent family information in compounding (e.g. Gagne 200I, Krott, Schreuder & Baayen 2002).
CC :	52452; 524
FD :	Accent; Nom composé; Phonologie; Algorithme; Analyse de corpus; Anglais
ED :	Stress; Compound noun; Phonology; Algorithm; Corpus analysis; English
SD :	Algoritmo
LO :	INIST-23826.354000509183000010
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Links to Exploration step

Francis:12-0245472

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, <sub>200</sub>
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Towards an exemplar-based model of stress in English noun-noun compounds

Towards an exemplar-based model of stress in English noun-noun compounds

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri