Semantic Connections in the Complex Sentences for Post-Editing Machine Translation in the Kazakh Language

Abstract

The problems of machine translation are constantly arising. While the most advanced translation platforms, such as Google and Yandex, allow for high-quality translations of languages with simple grammatical structures, more morphologically rich languages still suffer from the translation of complex sentences, and translation services leave many structural errors. This study focused on designing the rules for the grammatical structures of complex sentences in the Kazakh language, which has a difficult grammar with many rules. First, the types of complex sentences in the Kazakh language were thoroughly observed with the use of templates from the FuzzyWuzzy library. Then, the correction of complex sentences was completed with parallel corpora. The sentences were translated into English and Russian by existing machine translation systems. Therefore, the grammar of both Kazakh–English and Kazakh–Russian language pairs was considered. They both used the rules specifically designed for the post-editing steps. Finally, the performance of the developed algorithm was evaluated for an accuracy score for each pair of languages. This approach was then proposed for use in other corpora generation, post-editing, and analysis systems in future works.