Sarcasm is a form of figurative language where the intended meaning of a sentence differs from its literal meaning. This poses a serious challenge to several Natural Language Processing (NLP) applications such as Sentiment Analysis, Opinion Mining, and Author Profiling. In this paper, we present our participating system to the intended sarcasm detection task in English and Arabic languages. Our system\footnote{The source code of our system is available at \url{https://github.com/AbdelkaderMH/iSarcasmEval}} consists of three deep learning-based models leveraging two existing pre-trained language models for Arabic and English. We have participated in all sub-tasks. Our official submissions achieve the best performance on sub-task A for Arabic language and rank second in sub-task B. For sub-task C, our system is ranked 7th and 11th on Arabic and English datasets, respectively.

翻译：讽刺语是一种比喻语言,其用意与文字意义不同,对若干自然语言处理(NLP)应用,如感官分析、意见挖掘和作者剖析等,构成严重挑战。在本文中,我们用英语和阿拉伯语介绍我们的参与系统,以预定的讽刺语探测任务。我们的系统脚注{我们的系统源代码可在以下网址查阅:https://github.com/AbdelkaderMH/iSarcasmEval}由三种深层次的学习模型组成,利用两种现有的阿拉伯文和英文预先培训语言模型。我们参加了所有分任务。我们的官方文件在阿拉伯语分任务A和亚任务B分任务二等分任务上取得了最佳表现。关于子任务C,我们的系统在阿拉伯文和英文数据集上分别排在第7和第11位。