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Machine learning in translation corpora processing By Krzysztof Wolk.

By: Material type: TextTextPublication details: Boca Raton: CRC Press, c2019.Edition: 1Description: i-xv+264PISBN:
  • 9780367780203
Subject(s): DDC classification:
  • 491.858 022 102 85 WOL-M
Contents:
1: Introduction; 2: Statistical Machine Translation and Comparable Corpora; 3: State of the Art; 4: Author's Solutions to PL-EN Corpora Processing Problems;
Summary: This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by mining comparable corpora
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Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Computational Biology and Bioinformatics Processing Center Dept. of Computational Biology and Bioinformatics 491.858 022 102 85 WOL-M (Browse shelf(Opens below)) Available DCB4121

1: Introduction;
2: Statistical Machine Translation and Comparable Corpora;
3: State of the Art;
4: Author's Solutions to PL-EN Corpora Processing Problems;

This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by mining comparable corpora

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