Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media

Aleksandr Shatilov, Denis Gordeev, Alexey Rey


Abstract
This paper describes our approach to emphasis selection for written text in visual media as a solution for SemEval 2020 Task 10. We used an ensemble of several different Transformer-based models and cast the task as a sequence labeling problem with two tags: ‘I’ as ‘emphasized’ and ‘O’ as ‘non-emphasized’ for each token in the text.
Anthology ID:
2020.semeval-1.220
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venues:
COLING | SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
1685–1690
Language:
URL:
https://aclanthology.org/2020.semeval-1.220
DOI:
10.18653/v1/2020.semeval-1.220
Bibkey:
Cite (ACL):
Aleksandr Shatilov, Denis Gordeev, and Alexey Rey. 2020. Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1685–1690, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media (Shatilov et al., SemEval 2020)
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PDF:
https://aclanthology.org/2020.semeval-1.220.pdf