This paper describes our proposed system for the AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides. In this specific task, given the contents of a slide we are asked to predict the degree of emphasis to be laid on each word in the slide. We propose 2 approaches to this problem including a BiLSTM-ELMo approach and a transformers based approach based on RoBERTa and XLNet architectures. We achieve a score of 0.518 on the evaluation leaderboard which ranks us 3rd and 0.543 on the post-evaluation leaderboard which ranks us 1st at the time of writing the paper.
@article{arxiv.2101.11422,
title = {Cisco at AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides using Contextualized Embeddings},
author = {Sreyan Ghosh and Sonal Kumar and Harsh Jalan and Hemant Yadav and Rajiv Ratn Shah},
journal= {arXiv preprint arXiv:2101.11422},
year = {2021}
}
Comments
7 pages, 5 figures, 10 tables Submitted as a part of CAD-21 workshop at AAAI-2021