Sarcasm pertains to the subtle form of language that individuals use to express the opposite of what is implied. We present a novel architecture for sarcasm generation with emoji from a non-sarcastic input sentence. We divide the generation task into two sub tasks: one for generating textual sarcasm and another for collecting emojis associated with those sarcastic sentences. Two key elements of sarcasm are incorporated into the textual sarcasm generation task: valence reversal and semantic incongruity with context, where the context may involve shared commonsense or general knowledge between the speaker and their audience. The majority of existing sarcasm generation works have focused on this textual form. However, in the real world, when written texts fall short of effectively capturing the emotional cues of spoken and face-to-face communication, people often opt for emojis to accurately express their emotions. Due to the wide range of applications of emojis, incorporating appropriate emojis to generate textual sarcastic sentences helps advance sarcasm generation. We conclude our study by evaluating the generated sarcastic sentences using human judgement. All the codes and data used in this study will be made publicly available.

翻译：反讽是语言中一种微妙的形式，人们通过它表达与隐含意义相反的内容。我们提出了一种新颖的架构，用于从非反讽输入句子中生成带表情符号的反讽表达。我们将生成任务分解为两个子任务：一个用于生成文本反讽，另一个用于收集与这些反讽句子相关的表情符号。文本反讽生成任务融入了反讽的两个关键要素：情感反转以及与语境相关的语义不一致，其中语境可能涉及说话者与听众之间共享的常识或一般知识。现有的大多数反讽生成工作都侧重于这种文本形式。然而，在现实世界中，当书面文本无法有效捕捉口语和面对面交流中的情感线索时，人们通常会选择表情符号来准确表达自己的情感。由于表情符号的广泛应用，融入合适的表情符号来生成文本反讽句子有助于推动反讽生成的发展。我们通过人工评估对所生成的反讽句子进行了验证。本研究中使用的所有代码和数据将公开发布。