Сөздерді туралау

We present a syntax-based statistical translation model. Our model trans- forms a source-language parse tree into a target-language string by apply- ing stochastic operations at each node. These operations capture …...

AbstractThe Joint Probability Model proposed by Marcu and Wong (2002) provides a probabilistic framework for modeling phrase-based statistical machine transla- tion (SMT). The model’s usefulness is, however, limited by the …...

We apply the Stat-XFER statistical transfer machine translation framework to the task of translating from French and German into En- glish. We introduce statistical methods within our framework that allow …...

We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to another. We propose quasi- …...

This paper proposes the use of a Determin- istic Annealing Expectation-Maximization (DAEM) algorithm to estimate the word- alignments involved in the statistical trans- lation process. This approach is aimed to …...

The translation model of statistical ma- chine translation systems is trained on par- allel data coming from various sources and domains. These corpora are usually con- catenated, word alignments are …...

We present a variant of phrase-based SMT that uses source-side parsing and a constituent re- ordering model based on word alignments in the word-aligned training corpus to predict hi- erarchical …...

While agreement-based joint training has proven to deliver state-of-the-art align- ment accuracy, the produced word align- ments are usually restricted to one-to- one mappings because of the hard cons- traint …...

AbstractResources for evaluating sentence-level and word-level alignment algorithms are unsatisfactory. Regarding sentence alignments, the existing data is too scarce, especially when it comes to difficult bitexts, containing instances of non-literal …...

AbstractWe present a study of the adequacy of current methods that are used for POS-tagging historical Dutch texts, as well as an exploration of the influence of employing different techniques …...

AbstractWord alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems, or to perform …...

AbstractThis report summarizes the Air Force Research Laboratory (AFRL) machine translation (MT) systems submitted to the news-translation task as part of the 2020 Conference on Machine Translation (WMT20) evaluation campaign. …...

AbstractWith the advent of end-to-end deep learning approaches in machine translation, interest in word alignments initially decreased; however, they have again become a focus of research more recently. Alignments are …...

AbstractWe present a novel approach to efficiently learn a simultaneous translation model with coupled programmer-interpreter policies. First, we present an algorithmic oracle to produce oracle READ/WRITE actions for training bilingual …...