Automatic Machine Translation of Poetry and a Low-Resource Language Pair

Abstract

Automatic machine translation is gaining more and more attention in a particular segment of the research community that treats various topics from artificial intelligence, natural language processing, computational linguistics, machine learning and data science. Machine translation is a complex task in which a computer is utilised for the purpose of translating from source to one or more target languages without human involvement, or with a minimum of interventions. In general, machine translation could be implemented in higher education and academic curricula in a variety of possible fields and applications. Although there are several approaches to machine translation, two are dominant today - statistical and neural machine translation. Both are being used in this research in form of two online machine translation systems. The aim of this paper is to examine the usability of machine translation for poetry and a low-resource language pair, such as Croatian-German. The authors chose to use a data set that contained the works of a relevant contemporary poet of the Croatian language and the translations of his poems in German that were conducted by two professional literary translators. The paper demonstrates the effectiveness of machine translation of poetry with regard to special automatic quality metrics.