Quality Assessment Of Machine Translation Output: Cognitive Evaluation Approach In An Eye Tracking Experiment

Despite fast development of machine translation, the output quality is less than acceptable in certain language pairs. The aim of this paper is to determine the types of errors in machine translation output that cause comprehension problems to potential readers. The study is based on a reading task experiment using eye tracking and a retrospective survey as a complementary method to add more value to the research as eye tracking as a method is considered to be problematic and challenging (O'BRIEN, 2009; ALVES et al., 2009). The cognitive evaluation approach is used in an eye tracking experiment to determine the complexity of the errors in the English-Lithuanian language pair from easiest to hardest as seen by the readers of a machine-translated text. The tested parameters - gaze time and fixation count - demonstrate that a different amount of cognitive effort is required to process different types of errors in machine-translated texts. The current work aims at contributing to other research in the Translation Studies field by providing the analysis of error assessment of machine translation output.