Ariadna Font Llitjós

Also published as: Ariadna Font Llitjos, Ariadna Font-Llitjos


2008

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Linguistic Structure and Bilingual Informants Help Induce Machine Translation of Lesser-Resourced Languages
Christian Monson | Ariadna Font Llitjós | Vamshi Ambati | Lori Levin | Alon Lavie | Alison Alvarez | Roberto Aranovich | Jaime Carbonell | Robert Frederking | Erik Peterson | Katharina Probst
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Producing machine translation (MT) for the many minority languages in the world is a serious challenge. Minority languages typically have few resources for building MT systems. For many minor languages there is little machine readable text, few knowledgeable linguists, and little money available for MT development. For these reasons, our research programs on minority language MT have focused on leveraging to the maximum extent two resources that are available for minority languages: linguistic structure and bilingual informants. All natural languages contain linguistic structure. And although the details of that linguistic structure vary from language to language, language universals such as context-free syntactic structure and the paradigmatic structure of inflectional morphology, allow us to learn the specific details of a minority language. Similarly, most minority languages possess speakers who are bilingual with the major language of the area. This paper discusses our efforts to utilize linguistic structure and the translation information that bilingual informants can provide in three sub-areas of our rapid development MT program: morphology induction, syntactic transfer rule learning, and refinement of imperfect learned rules.

2007

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Improving transfer-based MT systems with automatic refinements
Ariadna Font Llitjós | Jaime Carbonell | Alon Lavie
Proceedings of Machine Translation Summit XI: Papers

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A Walk on the Other Side: Using SMT Components in a Transfer-Based Translation System
Ariadna Font Llitjós | Stephan Vogel
Proceedings of SSST, NAACL-HLT 2007 / AMTA Workshop on Syntax and Structure in Statistical Translation

2006

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Can the Internet help improve Machine Translation?
Ariadna Font Llitjós
Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Doctoral Consortium

2005

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A framework for interactive and automatic refinement of transfer-based machine translation
Ariadna Font Llitjós | Jaime G. Carbonell | Alon Lavie
Proceedings of the 10th EAMT Conference: Practical applications of machine translation

2004

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A trainable transfer-based MT approach for languages with limited resources
Alon Lavie | Katharina Probst | Erik Peterson | Stephan Vogel | Lori Levin | Ariadna Font-Llitjos | Jaime Carbonell
Proceedings of the 9th EAMT Workshop: Broadening horizons of machine translation and its applications

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The Translation Correction Tool: English-Spanish User Studies
Ariadna Font Llitjós | Jaime Carbonell
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Data Collection and Analysis of Mapudungun Morphology for Spelling Correction
Christian Monson | Lori Levin | Rodolfo Vega | Ralf Brown | Ariadna Font Llitjos | Alon Lavie | Jaime Carbonell | Eliseo Cañulef | Rosendo Huisca
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Error analysis of two types of grammar for the purpose of automatic rule refinement
Ariadna Font Llitjós | Katharina Probst | Jaime Carbonell
Proceedings of the 6th Conference of the Association for Machine Translation in the Americas: Technical Papers

This paper compares a manually written MT grammar and a grammar learned automatically from an English-Spanish elicitation corpus with the ultimate purpose of automatically refining the translation rules. The experiment described here shows that the kind of automatic refinement operations required to correct a translation not only varies depending on the type of error, but also on the type of grammar. This paper describes the two types of grammars and gives a detailed error analysis of their output, indicating what kinds of refinements are required in each case.

2002

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Evaluation and collection of proper name pronunciations online
Ariadna Font Llitjós | Alan W. Black
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

2000

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Lessons Learned from a Task-based Evaluation of Speech-to-Speech Machine Translation
Lori Levin | Boris Bartlog | Ariadna Font Llitjos | Donna Gates | Alon Lavie | Dorcas Wallace | Taro Watanabe | Monika Woszczyna
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)