Корпус EuroParl

We present a method for improving statistical machine translation perfor- mance by using linguistically motivated syntactic information. Our algo- rithm recursively decomposes source language sentences into syntactically simpler and shorter …...

AbstractThe more expressive and flexible a base formalism for machine translation is, the less efficient parsing of it will be. However, even among formalisms with the same parse complexity, some …...

We propose a backoff model for phrase- based machine translation that translates unseen word forms in foreign-language text by hierarchical morphological ab- stractions at the word and the phrase level. …...

An important problem that is related to phrase-based statistical translation mod- els is the obtaining of word phrases from an aligned bilingual training corpus. In this work, we propose obtaining …...

We compare two pivot strategies for phrase-based statistical machine transla- tion (SMT), namely phrase translation and sentence translation. The phrase translation strategy means that we di- rectly construct a phrase …...

We describe the experiments of the UC Berke- ley team on improving English-Spanish ma- chine translation of news text, as part of the WMT’08 Shared Translation Task. We ex- periment …...

In this work we present a novel technique to rescore fragments in the Data-Oriented Translation model based on their contri- bution to translation accuracy. We de- scribe three new rescoring …...

We describe the system developed by the team of the National University of Singa- pore for English to Spanish machine trans- lation of News Commentary text for the WMT09 Shared …...

In this paper we address the task of transfer- ring FrameNet annotations from an English cor- pus to an aligned Italian corpus. Experiments were carried out on an English-Italian bitext …...

. This paper describes and evaluates the automatic grammatical annotation of a chat and an e-mail corpus of together 117 million words, using a modular Constraint Grammar system. We discuss …...

AbstractIn this article, we present an experiment of linguistic parameter tuning in the representation of the semantic space of polysemous words. We evaluate quantitatively the influence of some basic linguistic …...

AbstractThe identification of rare and novel senses is a challenge in lexicography. In this paper, we present a new method for finding such senses using a word aligned multilingual parallel …...

AbstractWe present our efforts to create a large-scale, semi-automatically annotated parallel corpus of cleft constructions. The corpus is intended to reduce or make more effective the manual task of finding …...

We present an empirical study of instance se- lection techniques for machine translation. In an active learning setting, instance selection minimizes the human effort by identifying the most informative sentences …...

We investigate a language model that com- bines morphological and shape features with a Kneser-Ney model and test it in a large crosslingual study of European languages. Even though the …...

AbstractThanks to their rich morphology, Italian and Spanish allow pro-drop pronouns, i.e., non lexically-realized subject pronouns. Here we distinguish between two different types of null subjects: personal pro-drop and impersonal …...

AbstractThis paper presents a method for verb phrase (VP) alignment in an English-French parallel corpus and its use for improving statistical machine translation (SMT) of verb tenses. The method starts …...

AbstractFollowing the pioneering work by (CITATION), we address in this paper the analysis of a family of quantitative comparability measures dedicated to the construction and evaluation of topical comparable corpora. …...

AbstractThis work presents parallel corpora automatically annotated with several NLP tools, including lemma and part-of-speech tagging, named-entity recognition and classification, named-entity disambiguation, word-sense disambiguation, and coreference. The corpora comprise both …...

AbstractWe describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available. This method makes …...

AbstractMultilingual machine translation addresses the task of translating between multiple source and target languages. We propose task-specific attention models, a simple but effective technique for improving the quality of sequence-to-sequence …...

AbstractThis study proposes a new neural machine translation (NMT) model based on the encoder-decoder model that incorporates named entity (NE) tags of source-language sentences. Conventional NMT models have two problems …...

AbstractHow language-agnostic are current state-of-the-art NLP tools? Are there some types of language that are easier to model with current methods? In prior work (Cotterell et al., 2018) we attempted …...

AbstractMultilingual neural machine translation with a single model has drawn much attention due to its capability to deal with multiple languages. However, the current multilingual translation paradigm often makes the …...