Analysis of complexity between spoken and written language for statistical machine translation in west-slavic group

Abstract

The multilingual nature of the world makes translation a crucial requirement today. Within this research we apply state of the art statistical machine translation techniques to the West-Slavic languages group. We do West-Slavic languages classification and choose Polish as a representative candidate for our research. The experiments are conducted on written and spoken texts, which characteristics are defined as well. The machine translation systems are trained within West-Slavic group as well as into English. Translation systems and data sets are analyzed, prepared and adapted for the needs of West-Slavic—* translation. To evaluate the effects of different preparations on translation results, we conducted experiments and used the BLEU, NIST and TER metrics. By defining proper translation parameters to morphologically rich languages we improve the translation quality and draw the conclusions.