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Czech-Slovak Statistical Machine Translation
Astaloš, Lukáš ; Kouřil, Jan (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to design, implement and evaluate the translation system capable of translating texts from Czech to Slovak language. It describes theoretical foundations of statistical machine translation and then the phase of design and development of system. The chosen strategy was to build phrase-based translation model using one large parallel corpus in combination with language model from local institute of linguistics. The statistical machine translation Moses was used to achieve this goal. The vocabulary translation of unknown words using stemming was proposed and tested. Precision of build system was evaluated with BLEU score and it achieved comparable results with other systems.
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Chatbot Based on Artificial Neural Networks
Richtarik, Lukáš ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
This work deals with the issue of chatbots, which are based on artificial neural networks and generative models. It also describes options and process of designing the chatbot as well as an implementation and testing using BLEU metrics. The work contains multiple experiments with different models of chatbots, their performance evaluation and comparison, user experience and several suggestions for future enhancements.
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Czech-Slovak Machine Translation
Mydliar, Ján ; Kouřil, Jan (referee) ; Smrž, Pavel (advisor)
This Master thesis deals with machine translation from Czech to Slovak. The first chapter motivates the work, the second discusses various approaches to machine translation and the third details evaluation of the methods. Chapter 4 introduces the design and implementation of my system, paying a special attention to a new parallel corpus that has been created. Chapter 5 summarizes testing and evaluation of the developed system.
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Machine Translation Using Artificial Neural Networks
Holcner, Jonáš ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
The goal of this thesis is to describe and build a system for neural machine translation. System is built with recurrent neural networks - encoder-decoder architecture in particular. The result is a nmt library used to conduct experiments with different model parameters. Results of the experiments are compared with system built with the statistical tool Moses.
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Czech-English Translation
Petrželka, Jiří ; Schmidt, Marek (referee) ; Smrž, Pavel (advisor)
Tato diplomová práce popisuje principy statistického strojového překladu a demonstruje, jak sestavit systém pro statistický strojový překlad Moses. V přípravné fázi jsou prozkoumány volně dostupné bilingvní česko-anglické korpusy. Empirická analýza časové náročnosti vícevláknových nástrojů pro zarovnání slov demonstruje, že MGIZA++ může dosáhnout až pětinásobného zrychlení, zatímco PGIZA++ až osminásobného zrychlení (v porovnání s GIZA++). Jsou otestovány tři způsoby morfologického pre-processingu českých trénovacích dat za použití jednoduchých nefaktorových modelů. Zatímco jednoduchá lemmatizace může snížit BLEU, sofistikovanější přístupy většinou BLEU zvyšují. Positivní efekty morfologického pre-processingu se vytrácejí s růstem velikosti korpusu. Vztah mezi dalšími charakteristikami korpusu (velikost, žánr, další data) a výsledným BLEU je empiricky měřen. Koncový systém je natrénován na korpusu CzEng 0.9 a vyhodnocen na testovacím vzorku z workshopu WMT 2010.
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Multi-source Text Summarization for Czech
Brus, Tomáš ; Bojar, Ondřej (advisor) ; Mareček, David (referee)
This work focuses on the summarization task for a set of articles on the same topic. It discusses several possible ways of summarizations and ways to assess their final quality. The implementation of the described algorithms and their application to selected texts constitutes a part of this work. The input texts come from several Czech news servers and they are represented as deep syntactic trees (the so called tectogrammatical layer).
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Chatbot Based on Artificial Neural Networks
Richtarik, Lukáš ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
This work deals with the issue of chatbots, which are based on artificial neural networks and generative models. It also describes options and process of designing the chatbot as well as an implementation and testing using BLEU metrics. The work contains multiple experiments with different models of chatbots, their performance evaluation and comparison, user experience and several suggestions for future enhancements.
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Machine Translation Using Artificial Neural Networks
Holcner, Jonáš ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
The goal of this thesis is to describe and build a system for neural machine translation. System is built with recurrent neural networks - encoder-decoder architecture in particular. The result is a nmt library used to conduct experiments with different model parameters. Results of the experiments are compared with system built with the statistical tool Moses.
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Multi-source Text Summarization for Czech
Brus, Tomáš ; Bojar, Ondřej (advisor) ; Mareček, David (referee)
This work focuses on the summarization task for a set of articles on the same topic. It discusses several possible ways of summarizations and ways to assess their final quality. The implementation of the described algorithms and their application to selected texts constitutes a part of this work. The input texts come from several Czech news servers and they are represented as deep syntactic trees (the so called tectogrammatical layer).
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Czech-Slovak Statistical Machine Translation
Astaloš, Lukáš ; Kouřil, Jan (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to design, implement and evaluate the translation system capable of translating texts from Czech to Slovak language. It describes theoretical foundations of statistical machine translation and then the phase of design and development of system. The chosen strategy was to build phrase-based translation model using one large parallel corpus in combination with language model from local institute of linguistics. The statistical machine translation Moses was used to achieve this goal. The vocabulary translation of unknown words using stemming was proposed and tested. Precision of build system was evaluated with BLEU score and it achieved comparable results with other systems.
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