Improving the Quality of Machine Translation Using the Reverse Model.

Skachkov, N. A.; Vorontsov, K. V.

Machine translation is a natural language text processing task that aims to automatically translate input text from one language into another language. The currently known machine translation models show a fairly high quality of translation between large languages, but for smaller language areas, represented by less data, the problem is still not solved. Different methods are used to deal with various errors in automatic translation systems. This paper discusses approaches that use translation models of reverse language directions and improve consistency between translations of the same text using direct and reverse translation models. The paper presents a general theoretical justification for such methods in terms of solving the likelihood maximization problem and also proposes a method for stable training of modern models using cyclic translations.

MACHINE translating; LANGUAGE & languages

Automation & Remote Control, 2022, Vol 83, Issue 12, p1897

0005-1179

Academic Journal

10.1134/S00051179220120049