Using Comparable Corpora for Under-Resourced Areas of Machine Translation

This book provides an overview of how comparable corpora can be used to overcome the lack of parallel resources when building machine translation systems for under-resourced languages and domains. It presents a wealth of methods and open tools for building comparable corpora from the Web, evaluating comparability and extracting parallel data that can be used for the machine translation task. It is divided into several sections, each covering a specific task such as building, processing, and using comparable corpora, focusing particularly on under-resourced language pairs and domains.

The book is intended for anyone interested in data-driven machine translation for under-resourced languages and domains, especially for developers of machine translation systems, computational linguists and language workers. It offers a valuable resource for specialists and students in natural language processing, machine translation, corpus linguistics and computer-assisted translation, and promotes the broader use of comparable corpora in natural language processing and computational linguistics.

Describes a step-by-step method for collecting comparable corpora and processing it for usage in machine translation Demonstrates how data from comparable corpora can improve the quality of machine translation Proposes novel methods for measuring the comparability of multilingual corpora Describes algorithms and techniques for alignment and extraction of lexical and terminological data from comparable corpora in order to provide training and customization data for machine translation

Autorentext
Prof. Inguna Skadia has been working on language technologies for over 25 years. Her research interests are in machine translation, human-computer interaction, and language resources and tools for under-resourced languages. She has coordinated and participated in many national and international projects related to human language technologies, and has authored or co-authored more than 60 peer-reviewed research papers.

Bogdan Babych is an Associate Professor of Translation Studies at the University of Leeds, UK. He holds a PhD in machine translation and in Ukrainian linguistics. Dr. Babych was a coordinator of the EU FP7 Marie Curie project HyghTra, and received a Leverhulme Early Career Fellowship for his project Translation Strategies in Comparable Corpora. He previously worked as a computational linguist at L&H Speech Products, Belgium.

Robert Gaizauskas is a Professor of Computer Science and head of the Natural Language Processing group, Department of Computer Science, University of Sheffield, UK. His research interests are in computational semantics, information extraction, text summarization and machine translation. He holds a DPhil from the University of Sussex, UK (1992), and has published more than 150 papers in peer-reviewed journals and conference proceedings.

Nikola Ljubei is an Assistant Professor at the Department of Information Science, University of Zagreb, Croatia, and researcher at the "Joef Stefan" Institute in Ljubljana, Slovenia. His main research interests are in language technologies for South Slavic languages, linguistic processing of non-standard texts, author profiling and social media analytics.

Prof. Dan Tufi, director of RACAI and full member of the Romanian Academy, has been active in computational and corpus linguistics for more than 30 years. His expertise is in tagging, word alignment, multilingual WSD, SMT, QA in open domains, lexical ontologies, language resource annotation and encoding. He has authored or co-authored more than 250 peer-reviewed papers, book chapters and books.

Andrejs Vasijevs is a co-founder and chairman of the board of Tilde, a leading European language technology and localization company. His expertise is in terminology management, machine translation and human computer interaction. He initiated and coordinated the ACCURAT project as well as several other international research and innovation projects. He holds a PhD in computer sciences from the University of Latvia and a Dr.h. from the Latvian Academy of Sciences.

Inhalt
Introduction.- Cross-language comparability and its Applications for MT (Bogdan Babych, Fangzhong Su, Anthony Hartley, Ahmet Aker, Monica Lestari Paramita, Paul Clough, Robert Gaizauskas).- Collecting comparable corpora (Monica Lestari Paramita, Ahmet Aker, Paul Clough, Robert Gaizauskas, Nikos Glaros, Nikos Mastropavlos, Olga Yannoutsou, Radu Ion, Dan tefnescu, Alexandru Ceauu, Dan Tufi and Judita Preiss).- Extracting data from comparable corpora (Mrcis Pinnis, Nikola Ljubei, Dan tefnescu, Inguna Skadia, Marko Tadi, Tatjana Gornostaja, pela Vintar, Darja Fier).- Mapping and aligning units from comparable corpora (Ahmet Aker, Alexandru Ceauu, Yang Feng, Robert Gaizauskas, Sabine Hunsicker, Radu Ion, Elena Irimia, Dan tefnescu, Dan Tufi).- Training, enhancing, evaluating and using MT-Systems with comparable data (Bogdan Babych, Yu Chen, Andreas Eisele, Sabine Hunsicker, Mrcis Pinnis, Inguna Skadia, Raivis Skadi, Gregor Thurmair, Andrejs Vasijevs, Mateja Verlic, Xiaojun Zhang).- New areas of application of comparable corpora (Reinhard Rapp, Vivian Xu, Michael Zock, Serge Sharoff, Richard Forsyth, Bogdan Babych, Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi).- Appendices (Ahmet Aker, Radu Ion, Nikos Mastropavlos, Monica Paramita, Mrcis Pinnis, Dan tefnescu, Fangzhong Su, Gregor Thurmair,Elena Irimia, Nikola Ljubei, Evangelos Kanoulas, Judita Preiss, Rob Gaizauskas, Paul Clough, Emma Barker, Nikos Glaros, Tiberiu Boro, Inguna Skadia, Andrejs Vasijevs).