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

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