Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"statistical machine translation"”.
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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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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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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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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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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 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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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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Combining linguistics and statistics for high-quality limited domain English-Chinese machine translation
… necessary to produce a computer spoken translation game for learning Mandarin Chinese in a relatively broad travel domain. Three main aspects are addressed: efficient Chinese parsing, high-quality English-Chinese machine translation, and how these technologies can be integrated into a …
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Machine translation through clausal syntax : a statistical approach for Chinese to English
… proved to be one of the greatest challenges in statistical machine translation. One reason is that such techniques usually work with sentences as flat strings of words, rather than explicitly attempting to parse any sort of hierarchical structural representation. Because even simple syntactic …
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Cross-Lingual Word Sense Disambiguation for Low-Resource Hybrid Machine Translation
… can be used to improve lexical selection for machine translation when translating from a resource- rich language into an under-resourced one, especially when relatively little bitext is avail- able. In CL-WSD, we perform word sense disambiguation, considering the senses of a word to be its …
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The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction
… of deep learning, research in many areas of machine learning is converging towards the same set of methods and models. For example, long short-term memory networks are not only popular for various tasks in natural language processing (NLP) such as speech recognition, machine translation, …
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Deep Learning for Code Generation using Snippet Level Parallel Data
… approaches like transformer based methods, statistical machine translation models, models inspired from natural language settings have been proposed and shown to be effective at tasks like code summarization, code synthesis and code translation. Multiple benchmark data sets have also been …
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New Data-Driven Approaches to Text Simplification
… of our extensive analysis of the phrase-based statistical machine translation (PB-SMT) approach to ATS reject the widespread assumption that the success of that approach largely depends on the size of the training and development datasets. They indicate more influential factors for the success …
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