Sarcasm is a form of figurative language that serves as a humorous tool for mockery and ridicule. We present a novel architecture for sarcasm generation with emoji from a non-sarcastic input sentence in English. 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 has been made publicly available.

翻译：讽刺是一种修辞性语言形式，常被用作嘲弄和戏谑的幽默工具。我们提出了一种新颖的架构，用于从英语非讽刺输入句子中生成带表情符号的讽刺文本。我们将生成任务分为两个子任务：一个用于生成文本讽刺，另一个用于收集与这些讽刺句子相关的表情符号。讽刺的两个关键要素被整合到文本讽刺生成任务中：效价反转和与上下文的语义不一致，其中上下文可能涉及说话者与听众之间共享的常识或一般知识。现有的讽刺生成研究大多聚焦于这种文本形式。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，人们常选择表情符号来准确表达情绪。由于表情符号的广泛应用，整合合适的表情符号来生成文本讽刺句子有助于推进讽刺生成研究。我们通过人工评估所生成的讽刺句子来总结本研究。本研究中使用的所有代码和数据均已公开发布。