A chatbot is perceived as more humanlike and likeable if it includes some jokes in its output. But most existing joke generators were not designed to be integrated into chatbots. This paper presents Witscript, a novel joke generation system that can improvise original, contextually relevant jokes, such as humorous responses during a conversation. The system is based on joke writing algorithms created by an expert comedy writer. Witscript employs well-known tools of natural language processing to extract keywords from a topic sentence and, using wordplay, to link those keywords and related words to create a punch line. Then a pretrained neural network language model that has been fine-tuned on a dataset of TV show monologue jokes is used to complete the joke response by filling the gap between the topic sentence and the punch line. A method of internal scoring filters out jokes that don't meet a preset standard of quality. Human evaluators judged Witscript's responses to input sentences to be jokes more than 40% of the time. This is evidence that Witscript represents an important next step toward giving a chatbot a humanlike sense of humor.
翻译:聊天机如果在其输出中包含一些笑话, 就会被视为更人性化和更可取。 但大多数现有的笑话生成器没有设计成可以融入聊天机。 本文展示了Witscript, 这是一种可以即兴制作原始的、 与背景相关的笑话的新型笑话生成系统, 比如在谈话过程中的幽默反应。 这个系统是基于专家喜剧作家创建的笑话写作算法。 Witstrict 使用众所周知的自然语言处理工具从主题句中提取关键词, 并使用文字游戏将这些关键字和相关词链接起来, 以创建一击线。 然后, 一个事先训练过的神经网络语言模型, 已经对电视剧单调笑话的数据集进行精细调, 用来填补主题句和拳行之间的差距, 来完成笑话的响应。 内部评分过滤器的方法是不符合预先设定的质量标准的笑话。 人类评价员认为Wittrint对输入句的反应是40%以上时间的笑话。 这是Wittpriduction代表了给予人性幽默的下一个重要步骤。