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Titlebook: Machine Translation with Minimal Reliance on Parallel Resources; George Tambouratzis,Marina Vassiliou,Sokratis Sofi Book 2017 The Author(s

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书目名称Machine Translation with Minimal Reliance on Parallel Resources
编辑George Tambouratzis,Marina Vassiliou,Sokratis Sofi
视频video
概述Introduces a novel language-independent method for developing Machine Translation (MT) systems.Includes various experiments and comparisons to other MT systems.Provides a detailed presentation of the
丛书名称SpringerBriefs in Statistics
图书封面Titlebook: Machine Translation with Minimal Reliance on Parallel Resources;  George Tambouratzis,Marina Vassiliou,Sokratis Sofi Book 2017 The Author(s
描述This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.​
出版日期Book 2017
关键词MT portability to new language pairs; Machine learning methods; Machine translation (MT); Non-reliance
版次1
doihttps://doi.org/10.1007/978-3-319-63107-3
isbn_softcover978-3-319-63105-9
isbn_ebook978-3-319-63107-3Series ISSN 2191-544X Series E-ISSN 2191-5458
issn_series 2191-544X
copyrightThe Author(s) 2017
The information of publication is updating

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Extensions to the PRESEMT Methodology,sed. The second extension involves the use of supplementary language models (LM) in the TL, to improve the translation accuracy in terms of both the phrasal level but also the post-editing and token generation steps.
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Extensions to the PRESEMT Methodology,in an effort to achieve gains in the translation accuracy, for which alternative implementations have been suggested. These extensions concern different modules of the PRESEMT architecture. The first extension covers the pre-processing stage, where an improved phrasing model for the SL side is propo
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