Abstrakt
The aim of the paper is to verify the influence of the used machine translation system on the level of sentiment in the translated text from Slovak to English using the available systems Google Translate and DeepL. The experiment was carried out on a parallel corpus created from subtitles of movies of different styles.
The raw parallel corpus contained subtitles in Slovak and English. IBM Watson Natural Language Understanding service was used to identify the sentiment in the subtitles of ten movies of different genres.
The paper also describes the methodology of preparing the dataset suitable for sentiment analysis using the IBM NLU service. The research showed a high correlation between human text and machine translation of subtitles for both translation systems.
The research results show a high level of onsistency of sentiment levels in both forms of translation. Based on the results obtained, the results of sentiment in machine translation can be generalized for the two most widely used translation systems.