Machine Translation with Minimal Reliance on Parallel Resources
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,
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George Tambouratzis Marina Vassiliou Sokratis Sofianopoulos
Machine Translation with Minimal Reliance on Parallel Resources 123
SpringerBriefs in Statistics
More information about this series at http://www.springer.com/series/8921
George Tambouratzis Marina Vassiliou Sokratis Sofianopoulos •
Machine Translation with Minimal Reliance on Parallel Resources
123
Sokratis Sofianopoulos Institute for Language and Speech Processing Athens Greece
George Tambouratzis Institute for Language and Speech Processing Athens Greece Marina Vassiliou Institute for Language and Speech Processing Athens Greece
ISSN 2191-544X SpringerBriefs in Statistics ISBN 978-3-319-63105-9 DOI 10.1007/978-3-319-63107-3
ISSN 2191-5458
(electronic)
ISBN 978-3-319-63107-3
(eBook)
Library of Congress Control Number: 2017947698 © The Author(s) 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Acknowledgements
The work presented in this book has originated from the PRESEMT project, which has comprised in total six partners, namely ILSP (Institute for Language and Speech Processing/Athena R.C.), GFAI (Gesellschaft zur Förderung der Angewandten Informationsforshung e.V.), NTNU (Norges Teknisk-Naturvitenskapelige Universitet), ICCS (Institute of Communication and Computer Systems), MU (Masaryk University) and LCL (Lexical Computing Ltd.). The concept of the PRESEMT methodology was conceived within the Machine Translation Department of ILSP, in a collaborative effort during early 2009. The novelty of the concept is that it attempts to circumvent the requirement for specialised resources and tools so as to support the creation of MT systems for diverse language pairs wi
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