ASSESSMENT OF THE QUALITY OF MACHINE TRANSLATION TEXT WITH USE A METHOD OF ANALYSIS OF FUZZY DUPLICATES
This article is devoted to problems of evaluation of machine translation quality. Modern methods and means of fully automatic machine translation is far from perfect, because when you translate a text from one natural language to another natural language, the semantic component is often lost in the translation and the result is often incorrect. The aim of the authors is to develop applications for automatic correction of machine translation to the level of publication. Currently, there are many methods and applications for evaluation of machine and automated translation involving the processing of parallel corpora. The disadvantage of these methods is the inability to track errors in a specific parallel corpus. The authors propose to use the results of reverse translation to evaluate the machine translation quality and to search the discrepancies, and comparing it with the original text with use the system identification of fuzzy duplicates, to search for inconsistencies in the parallel corpora and the subsequent adjustments. The modern methods of analysis of fuzzy duplicates in unstructured text that used to search for plagiarism are described. Classical methods of analysis of the text are divided into syntactic methods of analysis of sequences, consisting of characters, words, phrases or sentences and methods of lexical analysis and definition of the checksum words, phrases, sentences and paragraphs. These methods are reviewed for their use in the system of adjustments of machine translation. The novelty of this work is to develop schemes of work machine translator with automatic correction of discrepancies that identified by the described method. The prospects of using this method are analyzed.