Eyetracked Multi-Modal Translation (EMMT)
EMMT (Eyetracked Multi-Modal Translation) is a simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenarios.
We present EMMT, a dataset containing monocular eye movement recordings, audio data and 4-electrode wearable electroencephalogram (EEG) data of 43 participants while engaged in sight translation supported by an image.
The dataset can be found here: https://github.com/ufal/eyetracked-multi-modal-translation
The full description of the experiment design is in the paper accompanying the EMMT dataset (the link will be posted here soon).