Paper Info
Title
Slavic languages in phrase-based statistical machine translation: a survey
Abstract
The demand for translations is increasing at a rate far beyond the capacity of professional translators. It is too difficult, time consuming and expensive to translate everything from scratch in each language. Machine translation offers a solution, as it provides translation automatically. Until recently, statistical machine translation has proved to be one of the most successful approaches. However, a new approach to machine translation based on neural networks has emerged with promising results. The present paper concerns phrase-based statistical machine translation, an area that has been extensively studied in the literature. The translation system consists of many components built on the premise of probabilities. Each component is described separately. Although high quality translation systems have been developed for certain language pairs, there is still a large number of languages that cause many translation errors. Languages with a rich morphology pose an especially difficult challenge for research. We address one group of morphologically rich languages: Slavic languages, which constitute a relatively homogeneous family of languages characterized by rich, inflectional morphology. The present paper offers a comprehensive survey of approaches to coping with Slavic languages in different aspects of statistical machine translation. We observe that the interest of the community in research of more difficult languages is increasing and we believe that the translation quality of those languages will reach the level of practical use in the near future.
Year
DOI
Venue
2019
10.1007/s10462-017-9558-2
Artificial Intelligence Review
Keywords
Field
DocType
Statistical machine translation,Morphology,Slavic language,Inflection,Free word order
Rule-based machine translation,Example-based machine translation,Slavic languages,Second-generation programming language,Computer science,Machine translation,Synchronous context-free grammar,Machine translation software usability,Natural language processing,Artificial intelligence,Dynamic and formal equivalence
Journal
Volume
Issue
ISSN
51.0
1.0
1573-7462
Citations 
PageRank 
References 
0
0.34
99
Authors
2
Name
Order
Citations
PageRank
Mirjam Sepesy Maučec150626.34
Janez Brest2219090.76