Paraphrastic Reformulations in Spoken Corpora
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Paraphrastic Reformulations in Spoken Corpora
Auteur(s) :
Eshkol-Taravella, Iris [Auteur]
Laboratoire Ligérien de Linguistique [LLL]
Grabar, Natalia [Auteur correspondant]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Laboratoire Ligérien de Linguistique [LLL]
Grabar, Natalia [Auteur correspondant]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Titre de la revue :
Lecture Notes in Computer Science
9th International Conference on NLP, PolTAL2014
9th International Conference on NLP, PolTAL2014
Pagination :
425-437
Éditeur :
Springer
Date de publication :
2014
ISSN :
0302-9743
Mot(s)-clé(s) en anglais :
Reformulation
Paraphrase
Spoken corpora
Paraphrase
Spoken corpora
Discipline(s) HAL :
Sciences de l'Homme et Société/Linguistique
Informatique [cs]
Informatique [cs]
Résumé en anglais : [en]
Our work addresses the automatic detection of paraphrastic reformulation in French spoken corpora. The proposed approach is syn-tagmatic. It is based on specific markers and the specificities of the spoken language. Manual ...
Lire la suite >Our work addresses the automatic detection of paraphrastic reformulation in French spoken corpora. The proposed approach is syn-tagmatic. It is based on specific markers and the specificities of the spoken language. Manual multi-dimensional annotation performed by two annotators provides fine-grained reference data. An automatic method is proposed in order to decide whether sentences contain or not paraphras-tic relations. The obtained results show up to 66.4% precision. Analysis of the manual annotations indicates that few paraphrastic segments show morphological modifications (inflection, derivation or compounding) and that the syntactic equivalence between the segments is seldom respected, as these usually belong to different syntactic categories.Lire moins >
Lire la suite >Our work addresses the automatic detection of paraphrastic reformulation in French spoken corpora. The proposed approach is syn-tagmatic. It is based on specific markers and the specificities of the spoken language. Manual multi-dimensional annotation performed by two annotators provides fine-grained reference data. An automatic method is proposed in order to decide whether sentences contain or not paraphras-tic relations. The obtained results show up to 66.4% precision. Analysis of the manual annotations indicates that few paraphrastic segments show morphological modifications (inflection, derivation or compounding) and that the syntactic equivalence between the segments is seldom respected, as these usually belong to different syntactic categories.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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