Using Comparable Corpora for Under-Resourced Areas of Machine Translation

Dan Tufiş (Hrsg.), Inguna Skadiņa (Hrsg.), Andrejs Vasiļjevs (Hrsg.), Bogdan Babych (Hrsg.), Nikola Ljubešić (Hrsg.), Robert Gaizauskas (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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.



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Schlagwörter

Comparable corpora, Multilingual processing, Parallel data extraction from comparable corpora, Domain adaptation, Under-resourced languages, Comparability metric, Machine translation, Term extraction