Application of POS Tagging in Machine Translation Evaluation
Konferenční objektpeer-reviewedpostprintSoubory
Datum publikování
2016
Autoři
Vedoucí práce
Oponent
Název časopisu
Název svazku
Vydavatel
Wolters Kluwer ČR, a. s.
Abstrakt
The aim of the paper is to present a process of natural language processing in its full extent as well as in machine translation from English language into Slovak as a representative of inflectional language. We aim at the data preparation phase for automatic evaluation of machine translation through POS tagging. The preparation phase for MT evaluation consists of several steps, but only the first step - creation of dataset-parallel corpus is deeply described. We focus on the source text collection of various styles and genres-dataset creation and machine translation collection. Two machine translation systems are used-web SMT Google translator API and MT@EC. As a morphology analyzing tool-TreeTagger is used. The process of dataset creation, which covers not only parallel corpora creation, but also creation of errors' database of Slovak words with morphological annotation, is analyzed. The main contribution consists of a novel approach to research of MT evaluation given by the POS tagging (machine learning methods), to identify differences between MT output and post-edited machine translation output. The ground essential of the research is machine translation errors analysis, their identification and classification, from English language into Slovak.
Rozsah stran
p. 471-479
ISSN
2464-7470
Trvalý odkaz na tento záznam
Projekt
SGS_2016_023/Ekonomický a sociální rozvoj v soukromém a veřejném sektoru
Zdrojový dokument
DIVAI 2016 ‐ 11th International Scientific Conference on Distance Learning in Applied Informatics
Vydavatelská verze
Přístup k e-verzi
Pouze v rámci univerzity
Název akce
DIVAI 2016 ‐ 11th International Scientific Conference on Distance Learning in Applied Informatics (02.05.2016 - 04.05.2016)
ISBN
978-80-7552-249-8
Studijní obor
Studijní program
Signatura tištěné verze
Umístění tištěné verze
Přístup k tištěné verzi
Klíčová slova
Natural language processing, Evaluation, Machine Translation quality, Sentence alignment, Tokenization, POS tagging, Evaluace, Kvalita strojového překladu, POS tagging, Tokenizace