Hybrid data-driven models of machine translation
نویسندگان
چکیده
منابع مشابه
A survey of Data Driven Machine Translation
Machine Translation (MT) refers to the use of computers for translating automatically from one language to another. The differences between source and target languages and the inherent ambiguity of the source language itself make MT a very difficult problem. Traditional approaches to MT have relied on humans giving linguistic knowledge in the form of rules to transform text. Given the vastness ...
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We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic latent semantic analysis (PLSA) are applied for the purpose of implementation of data-driven models in particular. These models are able to represent complex semantic structures of given contexts, like text passages. G...
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Transfer-Driven Machine Translation (TDMT) [1, 2] is a translation technique developed as a research project at ATR Interpreting Telecommunications Research Laboratories. In TDMT, translation is performed mainly by a transfer module which applies transfer knowledge to an input sentence. Other modules, such as lexical processing, analysis, contextual processing and generation, cooperate with the...
متن کاملLexicon-Driven Machine Translation
Machine Translation (MT) systems have historically relied upon explicit grammars in order to analyze the source text and reproduce it in the target language. In this paper, we argue for a style of MT in which the focus of processing is at the level of the lexicon, rather than the grammar. This approach to translation allows an analyzer to map source sentences into an interlingual form, which th...
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ژورنال
عنوان ژورنال: Machine Translation
سال: 2006
ISSN: 0922-6567,1573-0573
DOI: 10.1007/s10590-006-9015-5