1. Articles in category: Machine Translation

    7849-7872 of 8094 « 1 2 ... 325 326 327 328 329 330 331 ... 336 337 338 »
    1. Discriminative Reranking for Natural Language Parsing.

      Discriminative Reranking for Natural Language Parsing Michael Collins and Terry Koo Massachusetts Institute of Technology This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with associated probabilities that de ne an initial ranking of these parses. A second model then attempts to improve upon this initial ranking, using additional features of the tree as evidence. The strength
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    2. A Discriminative Model for Tree-to-Tree Translation.

      A Discriminative Model for Tree-to-Tree Translation Brooke Cowan MIT CSAIL brooke@csail.mit.edu Ivona Ku˘ erov´ c a MIT Linguistics Department kucerova@mit.edu Michael Collins MIT CSAIL mcollins@csail.mit.edu Abstract This paper proposes a statistical, treeto-tree model for producing translations. Two main contributions are as follows: (1) a method for the extraction of syntactic structures with alignment information from a parallel corpus of translations, and (2) use of a discriminative, fea
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    3. Chinese Syntactic Reordering for Statistical Machine Translation.

      Chinese Syntactic Reordering for Statistical Machine Translation Philipp Koehn Michael Collins Chao Wang MIT CSAIL School of Informatics MIT CSAIL 32 Vassar Street, Room 362 32 Vassar Street, Room G-484 2 Buccleuch Place, 5BP 2L2 Edinburgh, EH8 9LW, UK Cambridge, MA 02139, USA Cambridge, MA 02139, USA wangc@csail.mit.edu mcollins@csail.mit.edu pkoehn@inf.ed.ac.uk Abstract Syntactic reordering approaches are an effective method for handling word-order differences between source and target langua
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    4. Head-Driven Statistical Models for Natural Language Parsing

      HEAD-DRIVEN STATISTICAL MODELS FOR NATURAL LANGUAGE PARSING Michael Collins A DISSERTATION in Computer and Information Science Presented to the Faculties of the University of Pennsylvania in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy 1999 Professor Mitch Marcus Supervisor of Dissertation Professor Jean Gallier Graduate Group Chair COPYRIGHT Michael Collins 1999 Acknowledgements Mitch Marcus was a wonderful advisor. He gave consistently good advice, and all
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    5. Machine translation of online product support articles using a data-driven MT system.

      Machine translation of online product support articles using a data-driven MT system Stephen D. Richardson September 2004 Available Documents: Word 187KB At AMTA 2002, we reported on a pilot project to machine translate Microsoft's Product Support Knowledge Base into Spanish. The successful pilot has since resulted in the permanent deployment of both Spanish and Japanese versions of the knowledge base, as well as ongoing pilot projects for French and German. The translated articles in each case
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    6. Towards a Simple and Accurate Statistical Approach to Learning Translation Relationships among Words.

      Towards a Simple and Accurate Statistical Approach to Learning Translation Relationships among Words Robert C. Moore July 2001 Available Documents: PDF 57 KB We report on a project to derive word translation relationships automatically from parallel corpora. Our effort is distinguished by the use of simpler, faster models than those used in previous high-accuracy approaches. Our methods achieve accuracy on single-word translations that seems comparable to any work previously reported, up to near
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    7. Statistical Machine Translation Using Labeled Semantic Dependency Graphs.

      Statistical Machine Translation Using Labeled Semantic Dependency Graphs Anthony Aue; Arul Menezes; Robert Moore; Chris Quirk; Eric Ringger October 2004 Available Documents: PDF 120K We present a series of models for doing statistical machine translation based on labeled semantic dependency graphs. We describe how these models were employed to augment an existing example-based MT system, and present results showing that doing so led to a significant improvement in translation quality as measured
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    8. Training a Sentence-Level Machine Translation Confidence Measure.

      Training a Sentence-Level Machine Translation Confidence Measure Chris Quirk May 2004 Available Documents: PDF 240KB We present a supervised method for training a sentence level confidence measure on translation output using a human-annotated corpus. We evaluate a variety of machine learning methods. The resultant measure, while trained on a very small dataset, correlates well with human judgments, and proves to be effective on one task based evaluation. Although the experiments have only been r
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      Mentions: Lisbon Portugal
    9. Fast and Accurate Sentence Alignment of Bilingual Corpora.

      Fast and Accurate Sentence Alignment of Bilingual Corpora Robert C. Moore October 2002 Available Documents: PDF 60 KB We present a new method for aligning sentences with their translations in a parallel bilingual corpus. Previous approaches have generally been based either on sentence length or word correspondences. Sentence-length-based methods are relatively fast and fairly accurate. Word-correspondence-based methods are generally more accurate but much slower, and usually depend on cognates o
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    7849-7872 of 8094 « 1 2 ... 325 326 327 328 329 330 331 ... 336 337 338 »
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