SEECAT: Speech & Eye- tracking Enabled Computer Assisted Translation

Mercedes Garcia-Martinez (1) , Karan Singla , Aniruddha Tammewar , Bartolomé Mesa-Lao (1) , Ankita Thakur , M.A. Anusuya , Srinivas Banglore , Michaël Carl (1)

1 CBS - Copenhagen Business School [Copenhagen]

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.

Domaines: Informatique [cs]

Mercedes Garcia-Martinez, Karan Singla, Aniruddha Tammewar, Bartolomé Mesa-Lao, Ankita Thakur, et al.. SEECAT: Speech & Eye- tracking Enabled Computer Assisted Translation. European Association for Machine Translation: EAMT, 2014, Dubrovnik, Croatia. pp.81--88. ⟨hal-01433258⟩