Machine learning in translation corpora processing
Author(s)
Bibliographic Information
Machine learning in translation corpora processing
（A Science Publishers book）
CRC Press, c2019
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
Table of contents
Preface
Introduction
Background and context
Machine translation (MT)
Statistical machine translation and comparable corpora
Overview of SMT
Textual Components and Corpora
Moses Tool Environment For SMT
Aspects of SMT processing
Evaluation of SMT Quality
State of the Art
Current methods and results in spoken language translation
Recent methods in comparable corpora exploration
Author's solutions to PL-EN corpora processing problems
Parallel data mining improvements
Multi-threaded, Tuned and GPU-accelerated Yalign
Tuning of Yalign method
Minor improvements in mining for Wikipedia exploration
Parallel data mining using other methods
SMT Metric Enhancements
Alignment and filtering of corpora
Baseline system training
Description of experiments
Results and conclusions
Machine translation results
Evaluation of obtained comparable corpora
Quasi comparable corpora exploration
Other fields of MT techniques application
Final conclusions
References
by "Nielsen BookData"
