Using Comparable Corpora for Under-Resourced Areas of Machine Translation

Nonfiction, Reference & Language, Language Arts, Linguistics, Computers, Advanced Computing, General Computing
Cover of the book Using Comparable Corpora for Under-Resourced Areas of Machine Translation by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319990040
Publisher: Springer International Publishing Publication: February 6, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783319990040
Publisher: Springer International Publishing
Publication: February 6, 2019
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Global Challenges in Water Governance by
Cover of the book Game Theory for Security and Risk Management by
Cover of the book Phenomenology of the Winter-City by
Cover of the book Victims’ Rights in Flux: Criminal Justice Reform in Colombia by
Cover of the book Information Retrieval by
Cover of the book Software Engineering Trends and Techniques in Intelligent Systems by
Cover of the book Fifty Years of Fuzzy Logic and its Applications by
Cover of the book Interrogating the Neoliberal Lifecycle by
Cover of the book Next-Generation Therapies and Technologies for Immune-Mediated Inflammatory Diseases by
Cover of the book Regulatory Gaps in Baltic Sea Governance by
Cover of the book Remote Sensing and Modeling by
Cover of the book Application of Geochemical Tracers to Fluvial Sediment by
Cover of the book Plato’s Protagoras by
Cover of the book Islamic Marketing by
Cover of the book Bionanomaterials for Skin Regeneration by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy