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.
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
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