Nicolas Stroppa


2007

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Comparing rule-based and data-driven approaches to Spanish-to-Basque machine translation
Gorka Labaka | Nicolas Stroppa | Andy Way | Kepa Sarasola
Proceedings of Machine Translation Summit XI: Papers

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Bootstrapping Word Alignment via Word Packing
Yanjun Ma | Nicolas Stroppa | Andy Way
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

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Alignment-guided chunking
Yanjun Ma | Nicolas Stroppa | Andy Way
Proceedings of the 11th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages: Papers

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A cluster-based representation for multi-system MT evaluation
Nicolas Stroppa | Karolina Owczarzak
Proceedings of the 11th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages: Papers

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Exploiting source similarity for SMT using context-informed features
Nicolas Stroppa | Antal van den Bosch | Andy Way
Proceedings of the 11th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages: Papers

2006

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Example-Based Machine Translation of the Basque Language
Nicolas Stroppa | Declan Groves | Andy Way | Kepa Sarasola
Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers

Basque is both a minority and a highly inflected language with free order of sentence constituents. Machine Translation of Basque is thus both a real need and a test bed for MT techniques. In this paper, we present a modular Data-Driven MT system which includes different chunkers as well as chunk aligners which can deal with the free order of sentence constituents of Basque. We conducted Basque to English translation experiments, evaluated on a large corpus (270,000 sentence pairs). The experimental results show that our system significantly outperforms state-of-the-art approaches according to several common automatic evaluation metrics.

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MATREX: DCU machine translation system for IWSLT 2006.
Nicolas Stroppa | Andy Way
Proceedings of the Third International Workshop on Spoken Language Translation: Evaluation Campaign

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Du quatrième de proportion comme principe inductif : une proposition et son application à l’apprentissage de la morphologie [Inference with formal analogical proportions: application to the automatic learning of morphology]
Nicolas Stroppa | François Yvon
Traitement Automatique des Langues, Volume 47, Numéro 1 : Varia [Varia]

2005

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An Analogical Learner for Morphological Analysis
Nicolas Stroppa | François Yvon
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)

2004

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Analogies dans les séquences : un solveur à états finis
Nicolas Stroppa | François Yvon
Actes de la 11ème conférence sur le Traitement Automatique des Langues Naturelles. Posters

L’apprentissage par analogie se fonde sur un principe inférentiel potentiellement pertinent pour le traitement des langues naturelles. L’utilisation de ce principe pour des tâches d’analyse linguistique présuppose toutefois une définition formelle de l’analogie entre séquences. Dans cet article, nous proposons une telle définition et montrons qu’elle donne lieu à l’implantation efficace d’un solveur d’équations analogiques sous la forme d’un transducteur fini. Munis de ces résultats, nous caractérisons empiriquement l’extension analogique de divers langages finis, correspondant à des dictionnaires de quatre langues.