Articles

This paper presents the results of the WMT09 shared tasks, which included a translation task, a system combination task, and an evaluation task. We con- ducted a large-scale manual evaluation of 87 machine translation systems and 22 system combination entries. We used the ranking of these systems to measure how …...

We introduce a syntactically enhanced word alignment model that is more flex- ible than state-of-the-art generative word alignment models and can be tuned ac- cording to different end tasks. First of all, this model takes the advantages of both unsupervised and supervised word alignment approaches by obtaining anchor alignments from …...

Current approaches to statistical machine translation try to incorporate more struc- ture into the translation process by includ- ing explicit syntactic information in form of a formal grammar (with a possible, but not necessary, correspondence to a linguis- tic motivated grammar). These more struc- tured models incur into an increased …...

Recent research has shown that Phrase- Based Statistical Machine Translation (PB-SMT) systems can benefit from two enhancements: (i) using words and POS tags as context-informed features on the source side; and (ii) incorporating lexical syntactic descriptions in the form of su- pertags on the target side. In this work we …...

In this paper, we deal with the problem of a large number of unaligned words in auto- matically learned word alignments for ma- chine translation (MT). These unaligned words are the reason for ambiguous phrase pairs extracted by a statistical phrase-based MT system. In translation, this phrase am- biguity causes …...

We present a series of empirical studies aimed at illuminating more precisely the likely contribution of semantic roles in im- proving statistical machine translation ac- curacy. The experiments reported study several aspects key to success: (1) the fre- quencies of types of SMT errors where semantic parsing and role labeling …...

This article describes an initial statistical machine translation system between Bre- ton, a Celtic language spoken in France, and French. It also describes a method for leveraging existing resources from an incomplete rule-based machine translation system to improve the coverage and trans- lation quality of the statistical system by generating …...

The paper addresses the issue of MT knowledge acquisition and describes a new hybrid methodology for automatic extraction of multi-word nominal termi- nology. The approach is based on statisti- cal techniques merged into a strongly lexicalized Constraint Grammar para- digm. It is targeted at intelligent output and computationally attractive properties. …...

In this paper we address the problem of translating between languages with word order disparity. The idea of augmenting statistical machine translation (SMT) by using a syntax-based reordering step prior to translation, proposed in recent years, has been quite successful in improving trans- lation quality. We present a new tech- …...

Constraint satisfaction inference is pre- sented as a generic, theory-neutral infer- ence engine for machine translation. The approach enables the integration of many different solutions to aspects of the output space, including classification-based trans- lation models that take source-side context into account, as well as stochastic compo- nents such as …...

Translation is an indispensable process for socioeconomic and cultural development in a multilingual society. The use of translation tools such as translation memories and machine translation systems can be beneficial in supporting the human translator. Unfortunately, the availability of these tools is limited for resource-scarce languages. In this paper, we …...

Recent advances have allowed algorithms that learn from aligned natural language texts to exploit aligned sentences in more than two languages. We investigate ways of combining �N 2 � bilingual aligned cor- pora together to create a multilingual aligned corpus across N languages. As a result of the combination of …...

Statistically estimated phrase-based mod- els promised to further the state-of-the-art, however, several works reported a perfor- mance decrease with respect to heuristi- cally estimated phrase-based models. In this work we present a latent variable phrase-based translation model inspired by the hidden semi-Markov models, that does not degrade the system. Experimental …...

This paper investigates the idea of adapt- ing language models for phrases that have poor translation quality. We apply a se- lective adaptation criterion which uses a classifier to locate the most difficult phrase of each source language sentence. A spe- cial adapted language model is constructed for the highlighted …...

State-of-the-art statistical machine transla- tion systems make use of a large trans- lation table obtained after scoring a set of bilingual phrase pairs automatically ex- tracted from a parallel corpus. The num- ber of bilingual phrase pairs extracted from a pair of aligned sentences grows expo- nentially as the length …...

This paper describes the development of two prototype systems for machine trans- lation between North Sámi and Lule Sámi. Experiments were conducted in rule-based machine translation (RBMT), using the Apertium platform, and statistical ma- chine translation (SMT) using the Moses- decoder. The experiments show that both approaches have their advantages …...

In this paper we investigate possibili- ties of the development of a task-specific translation component for cross-language question answering. We focus on the optimization of phrase-based SMT for models trained on very limited data re- sources. We also look at the combina- tion of such systems with another approach based …...

A machine translated sentence is seldom completely correct. Confidence measures are designed to detect incorrect words, phrases or sentences, or to provide an esti- mation of the probability of correctness. In this article we describe several word- and sentence-level confidence measures rely- ing on different features: mutual informa- tion between …...

In this paper we describe an approach to target language modeling which is based on a large treebank. We assume a bag of bags as input for the target language gener- ation component, leaving it up to this com- ponent to decide upon word and phrase or- der. An experiment …...

Feature statistics normalization techniques have been shown to be very successful in improving the noise robustness of a speech recognition system. In this paper, we propose an associative scheme in order to obtain a more accurate estimate of the statistical information in these techniques. By properly integrating codebook and utterance …...