ABSTRACT A non-default interpretation is required whenever speakers creatively depart from established norms and defaults. But effective speakers do not travel alone when they move away from default meanings to novel, non-default destinations. Effective speakers bring their readers with them, sometimes by making the non-default destination the only meaningful destination that can be reached with an utterance, but other times by helpfully—if subtly—marking their utterances to facilitate the dislocation of words and meanings. We consider the relative utility of different indicators of non-defaultness in this article, ranging from the subtle to the overt. Our approach argues for the usefulness of machine-generated texts when quantitatively exploring aspects of human linguistic creativity, since machine-tooled utterances can better assure the consistency and comparability of novel utterances that are designed to offer strikingly original points of view. Within this mechanical framework, we measure the extent of the shift from default to non-default interpretations via the downshift from positive to negative affect in machine-generated ironic utterances. In using machine-generated texts, our approach and its results also argue for the possibility that intelligent machines can craft creative utterances of their own, and effectively communicate an ironic point-of-view to human readers.

中文翻译：

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我们明星中的“默认”：在讽刺话语中标明非默认

摘要每当发言者创造性地偏离既定规范和默认值时，就需要非默认解释。但是，当有效的演讲者从默认含义转移到新颖的非默认目的地时，他们不会独自旅行。有效的演讲者有时会将他们的读者带到他们身边，有时通过使非默认目的地成为唯一可以通过话语到达的有意义的目的地，但有时通过有益的（如果巧妙的话）标记他们的话语以促进单词和含义的错位。我们考虑了本文中不同非违约指标的相对效用，范围从微妙到公开。我们的方法论证了机器生成文本在定量探索人类语言创造力的各个方面时的有用性，因为机器加工的话语可以更好地确保旨在提供惊人原创观点的新颖话语的一致性和可比性。在这个机械框架内，我们通过机器生成的讽刺话语从正面影响到负面影响的下降来衡量从默认解释到非默认解释的转变程度。在使用机器生成的文本时，我们的方法及其结果也证明了智能机器可以制作自己的创造性话语，并有效地向人类读者传达具有讽刺意味的观点的可能性。我们通过机器生成的讽刺话语从正面影响到负面影响的下降来衡量从默认解释到非默认解释的转变程度。在使用机器生成的文本时，我们的方法及其结果也证明了智能机器可以制作自己的创造性话语，并有效地向人类读者传达具有讽刺意味的观点的可能性。我们通过机器生成的讽刺话语从正面影响到负面影响的下降来衡量从默认解释到非默认解释的转变程度。在使用机器生成的文本时，我们的方法及其结果也证明了智能机器可以制作自己的创造性话语，并有效地向人类读者传达具有讽刺意味的观点的可能性。