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Showing 1 to 20 of 35 for “"Statistical machine translation"”.
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Lexical syntax for statistical machine translation
Statistical Machine Translation (SMT) is by far the most dominant paradigm of Machine Translation. This can be justified by many reasons, such as accuracy, scalability, computational efficiency and fast adaptation to new languages and domains. However, current approaches of Phrase-based SMT lacks …
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Deep Syntax in Statistical Machine Translation
Statistical Machine Translation (SMT) via deep syntactic transfer employs a three-stage architecture, (i) parse source language (SL) input, (ii) transfer SL deep syntactic structure to the target language (TL), and (iii) generate a TL translation. The deep syntactic transfer architecture achieves a …
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Statistical machine translation with cascaded probabilistic transducers
Statistical machine translation is based on the idea to extract information from bilingual corpora, which can be used to generate new translations. The current work combines aspects from example-based machine translation and from grammar-based approaches, esp. bilingual regular grammars, to develop …
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Speech Adaptation Modeling for Statistical Machine Translation
Spoken language translation (SLT) exists within one of the most challenging intersections of speech and natural language processing. While machine translation (MT) has demonstrated its effectiveness on the translation of textual data, the translation of spoken language remains a challenge, largely …
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Using linguistic knowledge in statistical machine translation
… information to enhance the performance of statistical machine translation (SMT). One of the advantages of the statistical approach to machine translation is that it is largely language-agnostic. Machine learning models are used to automatically learn translation patterns from data. SMT can, …
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Constrained word alignment models for statistical machine translation
… is a fundamental and crucial component in Statistical Machine Translation (SMT) systems. Despite the enormous progress made in the past two decades, this task remains an active research topic simply because the quality of word alignment is still far from optimal. Most state-of-the-art word …
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Improving statistical machine translation using morpho-syntactic information
In the framework of statistical machine translation (SMT), correspondences between the words in the source and the target language are learned from bilingual corpora, and often little or no linguistic knowledge is used to structure the underlying models. The work presented in this thesis is …
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Phrase based statistical machine translation : models, search, training
Machine translation is the task of automatically translating a text from one natural language into another. In this work, we describe and analyze the phrase-based approach to statistical machine translation. In any statistical approach to machine translation, we have to address three problems: the …
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Exact Sampling and Optimisation in Statistical Machine Translation
In Statistical Machine Translation (SMT), inference needs to be performed over a high-complexity discrete distribution de ned by the intersection between a translation hypergraph and a target language model. This distribution is too complex to be represented exactly and one typically resorts to …
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A tree-to-tree model for statistical machine translation
In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine translation (MT). In a statistical tree-to-tree approach, first the source-language input is parsed into a syntactic tree structure; then the source-language tree is mapped to a target-language tree. This …
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Statistical machine translation : from single-word models to alignment templates
In this work, new approaches for machine translation using statistical methods are described. In addition to the standard source-channel approach to statistical machine translation, a more general approach based on the maximum entropy principle is presented. Various methods for computing …
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Linguistically Motivated Reordering Modeling for Phrase-Based Statistical Machine Translation
… is one of the most difficult aspects of Statistical Machine Translation (SMT), and an important factor of its quality and efficiency. While short and medium-range reordering is reasonably handled by the phrase-based approach (PSMT), long-range reordering still represents a challenge for …
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Integrating source-language context into log-linear models of statistical machine translation
The translation features typically used in state-of-the-art statistical machine translation (SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling …
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Word re-ordering and dynamic programming based search algorithm for statistical machine translation
In this work, a new search procedure for statistical machine translation (SMT) is proposed that is based on dynamic programming (DP). The starting point is a DP solution to the traveling salesman problem that works by jointly processing tours that visit the same subset of cities. For SMT, the …
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Word alignment and smoothing methods in statistical machine translation: Noise, prior knowledge and overfitting
… paraphrases, lexical semantics (or non-literal translations), named-entities, coreferences, and transliterations. The first discussion is about word alignment where we propose a MWE-sensitive word aligner. The second discussion is about the smoothing methods for a language model and a translation …
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The enhancement of machine translation for low-density languages using Web-gathered parallel texts.
… radio, television, newspapers, and the Internet. Translation into and out of these languages may offer a way for speakers of these languages to interact with the wider world, but current statistical machine translation models are only effective with a large corpus of parallel texts - texts in two …
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A translation framework for discovering word-like units from visual scenes and spoken descriptions
… for multimodal word discovery systems based on statistical machine translation (SMT) and neural machine translation (NMT). We extend the existing theoretical frameworks on unsupervised word discovery and demonstrate a class of effective models for end-to-end word discovery from image regions and …
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Robust machine translation for multi-domain tasks
… and extend the phrase-based approach to statistical machine translation. Due to improved concepts and algorithms, the quality of the generated translation hypotheses has been significantly improved in recent years. Still, the translation quality leaves a lot to be desired when going …
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Investigating the effects of controlled language on the reading and comprehension of machine translated texts: a mixed-methods approach
… of technical support documentation produced by a statistical machine translation system. Readability is operationalised here as the extent to which a text can be easily read in terms of formal linguistic elements; while comprehensibility is defined as how easily a text’s content can be understood …
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