摘要：
【目的】为了探讨生成式人工智能如何赋能科技论文的视频摘要创作与传播，分析人工智能生成内容（Artificial Intelligence Generated Content，AIGC）在期刊出版与传播应用中的优势与所面临的挑战。【方法】提出一种利用多种AIGC大模型辅助期刊封面设计以及视频摘要创作的方法，通过具体案例研究详细阐述利用Kimi AI生成剧本、智影数字人进行配音、即梦AI生成分镜视频以及PPT设计无底色文字的过程。深入分析AIGC辅助将文本摘要转化为视频摘要的意义、AIGC对新媒体编辑工作的影响以及AIGC在内容生成中的伦理挑战。【结果】AIGC技术在期刊封面设计和视频摘要创作中可显著提高工作效率和质量，降低生产成本，同时提升论文摘要的可读性和接受度。AIGC可促进期刊出版与新媒体传播之间的融合。然而，在内容生成过程中也面临偏见、信息泄露、可靠性和真实性等伦理挑战。【结论】生成式人工智能为期刊封面设计和科技论文视频摘要的创作与传播赋能，对新媒体编辑工作将产生深远影响。因此，需重视并妥善解决AIGC使用过程中潜在的伦理问题，以确保学术传播的有效性与权威性。
关键词:
生成式人工智能,
科技论文,
视频摘要,
应用挑战,
学术传播
Abstract:
［Purposes］ To explore how generative artificial intelligence empowers the creation and dissemination of video abstracts for scientific papers, we analyze the advantages and challenges faced by artificial intelligence generated content (AIGC) in journal publishing and dissemination applications. ［Methods］ A method was proposed that leveraged multiple AIGC models to assist in journal cover design and video abstract creation. Through specific case studies, the process of using Kimi AI to generate scripts, Zenvideo digital humans for dubbing, Jimeng AI to create storyboard videos, and PPT to design text without background was detailed. An in-depth analysis was provided on the significance of AIGC in transforming text abstracts into video abstracts, the impact of AIGC on new media editing work, and the ethical challenges surrounding AIGC generation. ［Findings］ AIGC technology significantly enhances work efficiency and quality in journal cover design and video abstract creation, reduces production costs, and improves the readability and acceptability of paper abstracts. AIGC promotes the integration of journal publishing and new media dissemination. However, challenges such as bias, information leakage, reliability, and authenticity emerge during content generation. ［Conclusions］ Generative artificial intelligence empowers the creation and dissemination of journal cover designs and video abstracts for scientific papers, profoundly impacting new media editing work. Therefore, it is crucial to recognize and address the potential ethical issues in AIGC usage to ensure the effectiveness and authority of academic dissemination.
Key words:
Generative artificial intelligence,
Scientific paper,
Video abstract,
Application challenge,
Academic dissemination
谭春林, 王维朗, 徐志武, 王建平. 生成式人工智能赋能科技论文视频摘要的实践与挑战[J]. 中国科技期刊研究, 2024, 35(12): 1767-1774.
TAN Chunlin, WANG Weilang, XU Zhiwu, WANG Jianping. Practice and challenges of empowering video abstracts of scientific papers with generative artificial intelligence[J]. Chinese Journal of Scientific and Technical Periodicals, 2024, 35(12): 1767-1774.