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WorldCist'17 - 5th World Conference on Information Systems and Technologies

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Automatic parallel data mining after bilingual document alignment

It has become essential to have precise translations of texts from different parts of the world, but it is often difficult to fill the translation gaps as quickly as might be needed. Undoubtedly, there are multiple dictionaries that can help in this regard, and various online translators exist to help cross this lingual bridge in many cases, but even these resources can fall short of serving their true purpose. The translators can provide a very accurate meaning of given words in a phrase, but they often miss the true essence of the language. The research presented here describes a method that can help close this lingual gap by extending certain aspects of the alignment task for WMT16. It is possible to achieve this goal by utilizing different classifiers and algorithms and by use of advanced computation. We carried out various experiments that allowed us to extract parallel data at the sentence level. This data proved capable of improving overall machine translation quality.

Author(s):

Krzysztof Wołk    
Polish Japanese Academy of Information Technology
Poland

Agnieszka Wołk    
Polish Japanese Academy of Information Technology
Poland

 

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