论文标题
X-Pudu在Semeval-2022任务6：英语和阿拉伯讽刺检测的多语言学习
X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection
论文作者
论文摘要
从人们的主观陈述中发现讽刺和言语讽刺对于理解他们的预期意义以及在社会情景中的真实情感和立场至关重要。本文介绍了参与Semeval-2022任务6的X-PUDU系统，即Isarcasmeval-英语和阿拉伯语中的预期讽刺检测，旨在在自然语言理解的各种情况下检测预期的讽刺。我们的解决方案Finetunes预先训练的语言模型，例如Ernie-M和Deberta，在多语言环境下，以识别来自阿拉伯语和英语文本的讽刺意味。我们的系统在43个中排名第二，在任务A中排名第92位：英语和阿拉伯语中的单句检测；任务B的22分之一中的第五名：英语的二进制多标签分类；在16名中的第一个，在任务C中的13分中的第五名：英语和阿拉伯语中的句子对检测。
Detecting sarcasm and verbal irony from people's subjective statements is crucial to understanding their intended meanings and real sentiments and positions in social scenarios. This paper describes the X-PuDu system that participated in SemEval-2022 Task 6, iSarcasmEval - Intended Sarcasm Detection in English and Arabic, which aims at detecting intended sarcasm in various settings of natural language understanding. Our solution finetunes pre-trained language models, such as ERNIE-M and DeBERTa, under the multilingual settings to recognize the irony from Arabic and English texts. Our system ranked second out of 43, and ninth out of 32 in Task A: one-sentence detection in English and Arabic; fifth out of 22 in Task B: binary multi-label classification in English; first out of 16, and fifth out of 13 in Task C: sentence-pair detection in English and Arabic.
