  We present the Eyetracked Multi-Modal Translation (EMMT) corpus, a dataset
containing monocular eye movement recordings, audio and 4-electrode
electroencephalogram (EEG) data of 43 participants. The objective was to
collect cognitive signals as responses of participants engaged in a number of
language intensive tasks involving different text-image stimuli settings when
translating from English to Czech.
  Each participant was exposed to 32 text-image stimuli pairs and asked to (1)
read the English sentence, (2) translate it into Czech, (3) consult the image,
(4) translate again, either updating or repeating the previous translation. The
text stimuli consisted of 200 unique sentences with 616 unique words coupled
with 200 unique images as the visual stimuli.
  The recordings were collected over a two week period and all the participants
included in the study were Czech natives with strong English skills. Due to the
nature of the tasks involved in the study and the relatively large number of
participants involved, the corpus is well suited for research in Translation
Process Studies, Cognitive Sciences among other disciplines.
