  This paper describes the system proposed for addressing the research problem
posed in Task 10 of SemEval-2020: Emphasis Selection For Written Text in Visual
Media. We propose an end-to-end model that takes as input the text and
corresponding to each word gives the probability of the word to be emphasized.
Our results show that transformer-based models are particularly effective in
this task. We achieved the best Matchm score (described in section 2.2) of
0.810 and were ranked third on the leaderboard.

Computation and Language;Artificial Intelligence;Machine Learning