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Humor meets morality: Joke generation based on moral judgement

机译:幽默符合道德:基于道德判断的笑话生成

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摘要

Although humor enriches human lives, some jokes fail to amuse people because of a lack of morality. In this paper, we propose a mechanism capable of selecting humor based on moral criteria. To this end, we first construct a model based on an N-gram corpus and generate joke candidates using various template patterns. We then employ a moral judgement classifier based on a recurrent neural network and utilize the trained model for humor selection. The experimental results obtained from best-worst scaling demonstrate that this scheme is able to generate jokes with moral category labels. We confirmed that jokes about the classifier categorized as Loyally and Authority, which are regarded as good in our study, are funnier than jokes about Fairness, Purity, Harm, Cheating, and Degradation. Although we did not confirm that there was a difference in the funny level between good and bad moral jokes, the results demonstrate that moral categories of humor can affect the funny level.
机译:虽然幽默丰富了人类的生活,但有些笑话没有因为缺乏道德而娱乐人。 在本文中,我们提出了一种能够基于道德标准选择幽默的机制。 为此,我们首先根据n-gram语料库构建模型,并使用各种模板模式生成笑话候选。 然后,我们基于经常性神经网络使用道德判断分类器,并利用训练模型来幽默选择。 从最佳缩放中获得的实验结果表明,该方案能够通过道德类标签产生笑话。 我们证实,关于谈论忠于和权威的分类器的笑话在我们的研究中被视为良好,而是比公平,纯洁,伤害,作弊和退化的笑话更有趣。 虽然我们没有证实有趣的道德笑话之间有趣的水平有所不同,但结果表明,幽默的道德类别会影响有趣的水平。

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