Translation Quality Assessment of Google Translate in Translating Audiovisual Based on House s (2015) Model: The Case of Lucifer

Translation machines were presented many years ago and have had a great advancement in the recent decades. Google Translate is one of the most widely-known translation machines which is now used frequently. The present study sought to assess the quality of Google Translate in rendering audio-visual texts. To do so, the first 5 episodes of Lucifer series were randomly selected as the corpus of the study. The original text translated by Google Translate was compared and contrasted with the human translation in order to find matches and mismatches. The House s (2015) TQA model was picked up as the analytical framework of the study since it has proven to be quite applicable in covering different genres of texts. The results of the study revealed that Google Translate was not of much help in rendering audio-visual texts as it failed to translate most of the sentences, clauses and even words properly. The analysis showed a considerable difference between the two translations by Google Translate and human translation. The mismatches were mostly in micro-level especially words and structures. In addition, it was found that Google Translate was able to translate simple and short sentences and structures accurately and thus cannot be relied on in rendering complex structures and words with ambiguity or several meanings. Generally speaking, Google Translate cannot replace human translation since it translates literally.