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We discuss phrase-based statistical machine translation performance enhancing techniques which have proven effective for Japanese-to-English and Chinese-to- English translation of BTEC corpus. We also address some issues that arise in …...

AbstractMANOS (Multilingual Application Network for Olympic Services) project. aims to provide intelligent multilingual information services in 2008 Olympic Games. By narrowing down the general language technology, this paper gives an …...

. The merit of phrase-based statistical machine translation is often reduced by the complexity to construct it. In this paper, we ad- dress some issues in phrase-based statistical machine translation, …...

We present a novel approach for the automatic translation of written text into sign language. A new corpus focussing on the weather report domain for the language pair German and …...

This paper presents a maximum entropy ma- chine translation system using a minimal set of translation blocks (phrase-pairs). While recent phrase-based statistical machine trans- lation (SMT) systems achieve significant im- …...

We provide an in-depth analysis of the in- tegration of an Arabic-to-English translit- eration system into a general-purpose phrase-based statistical machine translation system. We study the integration from dif- ferent …...

This paper proposes a novel method for phrase-based statistical machine translation by using pivot language. To conduct trans- lation between languages Lf and Le with a small bilingual corpus, we …...

Until quite recently, extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic structure caused system per- formance to deteriorate. In this work we show that incorporating lexical syntactic de- scriptions in …...

. The Phrase-Based Statistical Machine Translation (PB-SMT) model has recently begun to include source context modeling, under the assumption that the proper lexical choice of an ambiguous word can be …...

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 …...

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; …...

This study evaluates the impact of inte- grating two different collocation segmen- tations methods in a standard phrase-based statistical machine translation approach. The collocation segmentation techniques are implemented simultaneously in …...

This paper describes how to cluster to- gether the phrases of a phrase-based sta- tistical machine translation (SMT) sys- tem, using information in the phrase table itself. The clustering is …...

Several attempts have been made to learn phrase translation probabilities for phrase- based statistical machine translation that go beyond pure counting of phrases in word-aligned training data. Most approaches report …...

In extant phrase-based statistical machine translation (SMT) systems, the transla- tion model relies on word-to-word align- ments, which serve as constraints for the subsequent heuristic extraction and scor- ing processes. …...

In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two ex- tensions to standard n-gram language mod- els …...

In this paper we describe the Institute for Logic, Language and Computation (Uni- versity of Amsterdam) phrase-based statisti- cal machine translation system for English- to-German translation proposed within the EMNLP-WMT …...

This paper presents an integrated, end-to-end approach to online spelling correction for text input. Online spelling correction refers to the spelling correction as you type, as opposed to post-editing. The …...

The search space of Phrase-Based Statisti- cal Machine Translation (PBSMT) systems can be represented under the form of a di- rected acyclic graph (lattice). The quality of this search space …...

In this paper, we address statistical ma- chine translation of public conference talks. Modeling the style of this genre can be very challenging given the shortage of available in-domain training …...

The performance of Phrase-Based Statis- tical Machine Translation (PBSMT) sys- tems mostly depends on training data. Many papers have investigated how to cre- ate new resources in order to increase …...

We describe the systems developed by the team of the Qatar Computing Research Insti- tute for the WMT12 Shared Translation Task. We used a phrase-based statistical machine translation model with …...

In this paper, we propose a novel semantic cohesion model. Our model utilizes the predicate- argument structures as soft constraints and plays the role as a reordering model in the …...

We estimate the parameters of a phrase- based statistical machine translation sys- tem from monolingual corpora instead of a bilingual parallel corpus. We extend exist- ing research on bilingual lexicon …...

Lexicalized reordering model plays a central role in phrase-based statistical machine translation sys- tems. The reordering model specifies the orientation for each phrase and calculates its probability con- ditioned on …...

In phrase-based statistical machine trans- lation systems, variation in grammatical structures between source and target lan- guages can cause large movements of phrases. Modeling such movements is cru- cial in …...

We describe the system entered by the National Research Council Canada in the SemEval-2014 L2 writing assistant task. Our system relies on a standard Phrase-Based Statistical Machine Transla- tion trained …...

We investigate how to improve bilingual embedding which has been successfully used as a feature in phrase-based sta- tistical machine translation (SMT). De- spite bilingual embedding’s success, the contextual information, …...

We present a novel segmentation ap- proach for Phrase-Based Statistical Ma- chine Translation (PB-SMT) to languages where word boundaries are not obviously marked by using both monolingual and bi- lingual …...

AbstractReordering poses a big challenge in statistical machine translation between distant language pairs. The paper presents how reordering between distant language pairs can be handled efficiently in phrase-based statistical machine …...

AbstractThe phrase table is considered to be the main bilingual resource for the phrase-based statistical machine translation (PBSMT) model. During translation, a source sentence is decomposed into several phrases. The …...

AbstractIn this paper, we propose a new decoding method for phrase-based statistical machine translation which directly uses multiple preordering candidates as a graph structure. Compared with previous phrase-based decoding methods, …...

Neural Machine Translation (NMT) is known to outperform Phrase Based Sta- tistical Machine Translation (PBSMT) for resource rich language pairs but not for resource poor ones. Transfer Learning (Zoph et …...

Hybrid machine translation (HMT) takes advantage of different types of machine translation (MT) systems to improve translation performance. Neural machine translation (NMT) can produce more fluent translations while phrase-based statistical …...

Superiority of neural machine translation (NMT) and phrase-based statistical machine transla- tion (PBSMT) depends on the translation task. For some translation tasks, such as those involv- ing low-resource language pairs …...

AbstractNeural Machine Translation (NMT) has achieved promising results comparable with Phrase-Based Statistical Machine Translation (PBSMT). However, to train a neural translation engine, much more powerful machines are required than those …...

AbstractMachine Translation (MT) is one of the most important natural language processing applications. Independently of the applied MT approach, a MT system automatically generates an equivalent version (in some target …...

AbstractThis paper proposes an approach to cross-language sentence selection in a low-resource setting. It uses data augmentation and negative sampling techniques on noisy parallel sentence data to directly learn a …...