EUROPARL

AbstractTransBooster is a wrapper technology designed to improve the performance of wide-coverage machine translation systems. Using linguistically motivated syntactic information, it automatically decomposes source language sentences into shorter and syntactically …...

Mixture modelling is a standard technique for density estimation, but its use in sta- tistical machine translation (SMT) has just started to be explored. One of the main advantages of …...

In this paper, we present a Bayesian Learn- ing based method to train word dependent transition models for HMM based word alignment. We present word alignment re- sults on the …...

We describe the Cambridge University En- gineering Department phrase-based statisti- cal machine translation system for Spanish- English and French-English translation in the ACL 2008 Third Workshop on Statistical Ma- chine …...

This paper describes our statistical machine translation systems based on the Moses toolkit for the WMT08 shared task. We address the Europarl and News conditions for the follow- ing language …...

This paper reports on the participation of the TALP Research Center of the UPC (Universitat Politècnica de Catalunya) to the ACL WMT 2008 evaluation campaign. This year’s system is the …...

We present a new phrase-based con- ditional exponential family translation model for statistical machine translation. The model operates on a feature repre- sentation in which sentence level transla- tions are …...

We propose a language-independent approach for improving statistical machine translation for morphologically rich languages using a hybrid morpheme-word representation where the basic unit of translation is the morpheme, but word …...

AbstractMost of the research on the extraction of idiomatic multiword expressions (MWEs) focused on the acquisition of MWE types. In the present work we investigate whether a text instance of …...

AbstractThis paper profiles the Europarl part of an English-Swedish parallel corpus and compares it with three other subcorpora of the same parallel corpus. We first describe our method for comparison …...

In this paper we present a na¨ıve approach to tackle the problem of cross-lingual WSD and cross-lingual lexical substitu- tion which correspond to the Task #2 and #3 of the …...

Representing documents by vectors that are independent of language enhances machine translation and multilingual text categoriza- tion. We use discriminative training to create a projection of documents from multiple lan- …...

Resolving coordination ambiguity is a clas- sic hard problem. This paper looks at co- ordination disambiguation in complex noun phrases (NPs). Parsers trained on the Penn Treebank are reporting impressive …...

AbstractThis paper describes methods and results for the annotation of two discourse-level phenomena, connectives and pronouns, over a multilingual parallel corpus. Excerpts from Europarl in English and French have been …...

Domain adaptation boosts translation quality on in-domain data, but translation quality for domain adapted systems on out-of-domain data tends to suffer. Users of web-based translation services expect high quality translation …...

AbstractWe describe in this paper a hybrid ap-proach to build automatically bilingual lexicons of Multiword Expressions (MWEs) from parallel corpora. We more specifically investigate the impact of using a domain-specific …...

AbstractThe naive approach to annotation projection is not effective to project discourse annotations from one language to another because implicit relations are often changed to explicit ones and vice-versa in …...

AbstractUnseen words, also called out-of-vocabulary words (OOVs), are difficult for machine translation. In neural machine translation, byte-pair encoding can be used to represent OOVs, but they are still often incorrectly …...

AbstractGeneralization and reliability of multilingual translation often highly depend on the amount of available parallel data for each language pair of interest. In this paper, we focus on zero-shot generalization—a …...

AbstractOne key ingredient of neural machine translation is the use of large datasets from different domains and resources (e.g. Europarl, TED talks). These datasets contain documents translated by professional translators …...

AbstractMultilingual neural machine translation can translate unseen language pairs during training, i.e. zero-shot translation. However, the zero-shot translation is always unstable. Although prior works attributed the instability to the domination …...

AbstractDespite impressive progress in machine translation in recent years, it has occasionally been argued that current systems are still mainly based on pattern recognition and that further progress may be …...