Persoon
In this paper we describe the Institute for Logic, Language and Computation (University of Amsterdam) phrase-based statistical machine translation system for Englishto- German translation proposed within the EMNLP-WMT 2011 shared task. The main novelty of the submitted system is a syntaxdriven pre-t
How well can a phrase translation model perform if we permute the source words to fit target word order as perfectly as word alignment might allow? And how well would it perform if we limit the allowed permutations to ITGlike tree-transduction operations on the source parse tree? First we contribute
A challenging aspect of Statistical Machine Translation from Arabic to English lies in bringing the Arabic source morpho-syntax to bear on the lexical as well as word-order choices of the English target string. In this article, we extend the feature-rich discriminative Direct Translation Model 2 (DT
Tree-based reordering constitutes an important motivation for the increasing interest in syntax-driven machine translation. It has often been argued that tree-based reordering might provide a more effective approach for bridging the word-order differences between source and target sentences. One maj
Until quite recently, extending phrase-based statistical machine translation (PBSMT) with syntactic knowledge caused system performance to deteriorate. The most recent successful enrichments of PBSMT with hierarchical structure either employ nonlinguistically motivated syntax for capturing hierarchi
Omhoog
Ga terug naar de inhoud
Ga terug naar de site navigatie