In this paper we present an opensource machine translation toolkit Chaski which is ca-pable of training phrase-based machine translation models on Hadoop clusters. The toolkit provides a full training pipeline including distributed word alignment, word clustering and phrase extraction. The toolkit also provides an extended error-tolerance mechanism over stan-dardHadoop error-tolerance framework. The paper will describe the underlyingmethodology and the design of the system, together with instructions of how to run the system on Hadoop clusters. 1
Language models (LMs) are an essential element in statistical approaches to natural language process...
A basic task in machine translation is to choose the right translation for source words with several...
In this thesis, we explore and present machine learning (ML) approaches to a particularly challengin...
In this paper, we present the architecture of a distributed resource repository developed for collec...
Machine translation is the application of machines to translate text or speech from one natural lang...
The current trends in the translator training are shown, which reflect the orientation towards the u...
We believe that machine translation (MT) must be introduced to translation students as part of their...
The paper deals with the possibilities of using the Memsource system as the main component of a clou...
Language models (LMs) are an essential element in statistical approaches to natural language process...
This paper presents the work on Machine Translation (MT) that has been conducted within the KConnect...
Machine Translation Using Syntactic Analysis Martin Popel This thesis describes our improvement of m...
Machine translation is the task of automatically translating a text from one natural language into a...
We present a method for improving machine translation (MT) evaluation by targeted paraphrasing of r...
2019-02-14We provide new tools and techniques for improving machine translation for low-resource lan...
We introduce Z-MERT, a soware tool for minimum error rate training of machine translation sys-tems (...
Language models (LMs) are an essential element in statistical approaches to natural language process...
A basic task in machine translation is to choose the right translation for source words with several...
In this thesis, we explore and present machine learning (ML) approaches to a particularly challengin...
In this paper, we present the architecture of a distributed resource repository developed for collec...
Machine translation is the application of machines to translate text or speech from one natural lang...
The current trends in the translator training are shown, which reflect the orientation towards the u...
We believe that machine translation (MT) must be introduced to translation students as part of their...
The paper deals with the possibilities of using the Memsource system as the main component of a clou...
Language models (LMs) are an essential element in statistical approaches to natural language process...
This paper presents the work on Machine Translation (MT) that has been conducted within the KConnect...
Machine Translation Using Syntactic Analysis Martin Popel This thesis describes our improvement of m...
Machine translation is the task of automatically translating a text from one natural language into a...
We present a method for improving machine translation (MT) evaluation by targeted paraphrasing of r...
2019-02-14We provide new tools and techniques for improving machine translation for low-resource lan...
We introduce Z-MERT, a soware tool for minimum error rate training of machine translation sys-tems (...
Language models (LMs) are an essential element in statistical approaches to natural language process...
A basic task in machine translation is to choose the right translation for source words with several...
In this thesis, we explore and present machine learning (ML) approaches to a particularly challengin...