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作 者:李公全 李智国[1] 李卫星[2] 高栋 LI Gong-quan;LI Zhi-guo;LI Wei-xing;GAO Dong(Unit 66132 of PLA,Beijing 100042,China;National University of Defense Technology,Changsha 410003,China)
机构地区:[1]中国人民解放军66132部队,北京100042 [2]国防科技大学,长沙410003
出 处:《中国电子科学研究院学报》2022年第10期935-942,958,共9页Journal of China Academy of Electronics and Information Technology
基 金:国家社科基金青年项目(2021-SKJJ-C-010)。
摘 要:自然语言生成(Natural Language Generation, NLG)是在自然语言理解、图像识别和视频分析等技术基础上利用人工智能和语言学方法生成自然语言文本的过程,近年来成为人工智能研究领域的热点,在军事领域也得到了较好的应用。文中提出了NLG技术的应用框架体系,阐述了文本到文本、数据到文本、图片到文本和视频到文本4个大类的关键技术和实现方法;归纳总结了机器翻译、辅助撰写、智能问答、战场监视、侦察解译等11个典型场景,为NLG技术在军事领域的实战化应用提供方向;从军事领域数据集缺失、现有NLG系统的实用性和抗毁性不足等方面,深入剖析了制约NLG技术军事应用的瓶颈问题,并提出对策建议,为NLG技术在军事领域的未来发展提供参考。Natural language generation(NLG) is the process of using artificial intelligence and linguistic methods to generate natural language texts on the basis of natural language understanding, image recognition and video analysis, etc. In recent years, it has become a hot spot in the field of artificial intelligence research and has also been well applied in the military field. This paper proposes the application framework system of NLG technology, and elaborates the key technologies and implementation methods of four major categories: text-to-text, data-to-text, picture-to-text, and video-to-text. This paper summarizes 11 typical scenarios such as machine translation, auxiliary writing, intelligent question-and-answer, battlefield surveillance, and reconnaissance interpretation, providing direction for the practical application of NLG technology in the military field. From the aspects of the lack of data sets in the military field and the lack of practicability and invulnerability of the existing NLG system, the bottleneck problems restricting the military application of NLG technology are deeply analyzed, and countermeasures and suggestions are proposed to provide reference for the future development of NLG technology in the military field.
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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