Articles

This work presents translation results for the three data sets made available in the shared task “Exploiting Parallel Texts for Statistical Machine Translation” of the HLT-NAACL 2006 Workshop on Statisti- cal Machine Translation. All results pre- sented were generated by using the N- gram-based statistical machine translation system which has …...

The Microsoft Research translation system is a syntactically informed phrasal SMT system that uses a phrase translation model based on dependency treelets and a global reordering model based on the source dependency tree. These models are combined with several other knowledge sources in a log-linear manner. The weights of the …...

Complex Language Models cannot be eas- ily integrated in the first pass decoding of a Statistical Machine Translation system – the decoder queries the LM a very large number of times; the search process in the decoding builds the hypotheses incremen- tally and cannot make use of LMs that analyze …...

This paper describes the open-source Phrase-Based Statistical Machine Transla- tion Decoder - Phramer. The paper also presents the UTD (HLTRI) system build for the WMT06 shared task. Our goal was to improve the translation quality by en- hancing the translation table and by pre- processing the source language text 1...

We present translation results on the shared task ”Exploiting Parallel Texts for Statistical Machine Translation” gener- ated by a chart parsing decoder operating on phrase tables augmented and general- ized with target language syntactic cate- gories. We use a target language parser to generate parse trees for each sentence on …...

Improvements to Portage and its partici- pation in the shared task of NAACL 2006 Workshop on Statistical Machine Trans- lation are described. Promising ideas in phrase table smoothing and global dis- tortion using feature-rich models are dis- cussed as well as numerous improvements in the software base. 1...

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 word phrases by means of a Stochastic Inver- sion Translation Grammar. Experiments on the shared task proposed in this work- …...

We present here the translation system we used in this year’s WMT shared task. The main objective of our participation was to test RAMSES, an open source phrase- based decoder. For that purpose, we used the baseline system made available by the organizers of the shared task1 to build the …...

This paper reports translation results for the “Exploiting Parallel Texts for Statis- tical Machine Translation” (HLT-NAACL Workshop on Parallel Texts 2006). We have studied different techniques to im- prove the standard Phrase-Based transla- tion system. Mainly we introduce two re- ordering approaches and add morphologi- cal information. 1...

The joint probability model proposed by Marcu and Wong (2002) provides a strong probabilistic framework for phrase-based statistical machine translation (SMT). The model’s usefulness is, however, limited by the computational complexity of estimat- ing parameters at the phrase level. We present the first model to use word align- ments for …...

We present two translation systems ex- perimented for the shared-task of “Work- shop on Statistical Machine Translation,” a phrase-based model and a hierarchical phrase-based model. The former uses a phrasal unit for translation, whereas the latter is conceptualized as a synchronous- CFG in which phrases are hierarchically combined using non-terminals. …...

State of the art in statistical machine trans- lation is currently represented by phrase- based models, which typically incorpo- rate a large number of probabilities of phrase-pairs and word n-grams. In this work, we investigate data compression methods for efficiently encoding n-gram and phrase-pair probabilities, that are usu- ally encoded …...

In this paper we present a novel method for deriving paraphrases during automatic MT evaluation using only the source and reference texts, which are necessary for the evaluation, and word and phrase alignment software. Using target language paraphrases produced through word and phrase alignment a number of alternative reference sentences …...

In statistical machine translation, large numbers of parallel sentences are required to train the model parameters. However, plenty of the bilingual language resources available on web are aligned only at the document level. To exploit this data, we have to extract the bilingual sentences from these documents. The common method …...

Word posterior probabilities are a com- mon approach for confidence estimation in automatic speech recognition and ma- chine translation. We will generalize this idea and introduce n-gram posterior prob- abilities and show how these can be used to improve translation quality. Addition- ally, we will introduce a sentence length model …...

In this paper we propose a generalization of the Stack-based decoding paradigm for Statistical Machine Translation. The well known single and multi-stack decoding algorithms defined in the literature have been integrated within a new formalism which also defines a new family of stack- based decoders. These decoders allows a tradeoff …...

We present discriminative reordering models for phrase-based statistical ma- chine translation. The models are trained using the maximum entropy principle. We use several types of features: based on words, based on word classes, based on the local context. We evaluate the overall performance of the reordering models as well as …...

In statistical machine translation, an align- ment defines a mapping between the words in the source and in the target sen- tence. Alignments are used, on the one hand, to train the statistical models and, on the other, during the decoding process to link the words in the source sentence …...

We investigate why weights from generative mod- els underperform heuristic estimates in phrase- based machine translation. We first propose a sim- ple generative, phrase-based model and verify that its estimates are inferior to those given by surface statistics. The performance gap stems primarily from the addition of a hidden segmentation …...

The Arabic language has far richer sys- tems of inflection and derivation than En- glish which has very little morphology. This morphology difference causes a large gap between the vocabulary sizes in any given parallel training corpus. Segmen- tation of inflected Arabic words is a way to smooth its highly …...