Linguistically Motivated Statistical Machine Translation Models and
This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential component
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nguistically Motivated Statistical Machine Translation Models and Algorithms
Linguistically Motivated Statistical Machine Translation
Deyi Xiong Min Zhang •
Linguistically Motivated Statistical Machine Translation Models and Algorithms
123
Min Zhang Soochow University Suzhou Jiangsu China
Deyi Xiong Soochow University Suzhou Jiangsu China
ISBN 978-981-287-355-2 DOI 10.1007/978-981-287-356-9
ISBN 978-981-287-356-9
(eBook)
Library of Congress Control Number: 2014956709 Springer Singapore Heidelberg New York Dordrecht London © Springer Science+Business Media Singapore 2015 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. Printed on acid-free paper Springer Science+Business Media Singapore Pte Ltd. is part of Springer Science+Business Media (www.springer.com)
To my daughter Keke Deyi Xiong To my daughters Gege and Tongtong Min Zhang
Acknowledgments
The first author is grateful to his wife Chiara for her endless love and support. He is also very grateful to his parents for their decades of hard work. This book serves as a testament to the considerable effort they’ve put into raising him. He appreciates loving phone calls from his grandfather-in-law for his kind encouragements and practical support from his parents-in-law. He dedicates this book to his angel Keke, the new joy of his life! The second author is grateful to his family for their great love and support. This work was supported by National Natural Science Foundation of China (Grant No. 61373095, 61403269 and 61432013), Natural Science Foundation of Jiangsu Province (Grant No. BK20140355). The first author would like to thank his friends and mentors from Institute of Computing Technology, China. We would like to express our gratitude to our former colleagues from Institute for Infocomm Research, Singapore. We cherish the friendship and memory of working with them. We also thank our colleagues from School of Computer Science and Technology, Soochow University, for their immense practical help. Finally, we are
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