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kdehumor at semeval-2020 task 7: a neural network model for detecting funniness in dataset humicroedit

2021-05-11 15:44:03
Rida Miraj, Masaki Aono
arXiv_AI
       
Abstract

This paper describes our contribution to SemEval-2020 Task 7: Assessing Humor in Edited News Headlines. Here we present a method based on a deep neural network. In recent years, quite some attention has been devoted to humor production and perception. Our team KdeHumor employs recurrent neural network models including Bi-Directional LSTMs (BiLSTMs). Moreover, we utilize the state-of-the-art pre-trained sentence embedding techniques. We analyze the performance of our method and demonstrate the contribution of each component of our architecture.

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URL

https://arxiv.org/abs/2105.05135

PDF

https://arxiv.org/pdf/2105.05135.pdf

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