SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation

Tiping has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance.