幽默计算及其应用研究

doi:10.6040/j.issn.1671-9352.0.2016.266

摘要/Abstract

摘要： 幽默作为一种特殊的语言表达方式,是生活中活跃气氛、化解尴尬的重要元素。随着人工智能的快速发展,如何利用计算机技术识别和生成幽默成为自然语言处理领域热门的研究内容之一,并逐渐形成一个新兴研究领域:幽默计算。幽默计算致力于利用自然语言处理技术理解和识别包含幽默的文本表达,挖掘幽默表达潜在的语义内涵,构建面向幽默表达的计算模型。首先对当前幽默计算的背景进行概述,阐明幽默的可计算性和幽默计算对于人工智能的意义;在此基础上,对幽默研究的发展情况进行回顾,给出幽默研究的语言学基础;然后综述当前幽默计算在幽默识别和幽默生成两个方面的进展情况,分别给出针对幽默识别和幽默生成的计算框架;最后,对幽默计算在聊天机器人、机器翻译、儿童教育软件和外语教学等多个自然语言处理任务中的应用前景和应用模式进行展望。希望通过对幽默计算及其应用研究的总结和概述,完善现有幽默计算模型,增进计算机对于自然语言的理解,推动人工智能的进一步发展。

关键词: 自然语言理解, 幽默计算, 幽默生成, 人工智能, 幽默识别

Abstract: Humor, as a special phenomenon of human communications, can warm up the atmosphere and eliminate embarrassment. In recent years, with the research development of artificial intelligence, research area related to how to model humorous expression using computers becomes a hot topic in natural language processing tasks, and evolves to become a new subject, called computational humor. Computational humor aims to recognize and interpret humorous expressions in context using natural language processing technologies, and construct humor based computational models. In this article, we firstly introduce the backgrounds of computational humor research and detail the reasons for which humor can be modeled using computers. After that, we review related research in two lines, humor recognition and humor generation, and give the computational procedure of them respectively. Finally, we introduce some applications of humor computing in different tasks, including chatting robots, machine translation, children teaching software and English teaching. Overall, we review the recent research work in the area of humor computing to motivate new ideas and broaden horizons for further research in this area, which can help computers understand the natural language of humans, and promote the development of artificial intelligence.

Key words: computational humor, humor recognition, humor generation, artificial intelligence, natural language understanding

中图分类号:

TP391

林鸿飞,张冬瑜,杨亮,徐博. 幽默计算及其应用研究[J]. 山东大学学报（理学版）, 2016, 51(7): 1-10.

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