Machine Learning in Translation Corpora Processing

 
 
CRC Press
  • erschienen am 25. Februar 2019
  • |
  • 280 Seiten
 
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
978-0-429-59077-1 (ISBN)
 

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.

  • Englisch
  • Milton
  • |
  • Großbritannien
Taylor & Francis Ltd
  • Für höhere Schule und Studium
37 schwarz-weiße und 4 farbige Abbildungen, 111 schwarz-weiße Tabellen
978-0-429-59077-1 (9780429590771)
weitere Ausgaben werden ermittelt

Krzysztof Wolk holds a PhD Eng. degree in Computer Science, and is a graduate of the Polish-Japanese Academy of Information Technology. He is currently an associate professor at the Cathedral of Multimedia at the same university. His research is mostly related to natural language processing and machine learning based on statistical methods, neural networks and deep learning; and is interested in IT and its challenges, and engages in interdisciplinary projects, particularly those related to HCI, UX, medicine and psychology.

In addition, he has worked as a lecturer at the Warsaw School of Photography & Graphic Design, and as an IT trainer. His specialties as a teacher are primarily deep learning, machine learning, natural language processing, computational linguistics, multimedia, HCI, UX, mobile applications, HTML 5, Adobe applications and server products from Apple and Microsoft.

As far as his didactic work is concerned, he leads classrooms at the faculty of computer science and at the new media art department at the Polish-Japanese Academy of Information Technology and he also used to lead classes and lectures at the Warsaw School of Photography & Graphic Design.

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

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