基于AIGC的媒体内容跨模态理解系统设计与实现  

Design and Implementation of a Cross Modal Understanding System for Media Content Based on AIGC

作　　者：高尚清 洪松虹 朱甲雄 张荣波 GAO Shangqing;HONG Songhong;ZHU Jiaxiong;ZHANG Rongbo(Zhejiang Media Group,Hangzhou 310005,China)

机构地区：[1]浙江广播电视集团,浙江杭州310005

出　　处：《电视技术》2025年第1期32-36,共5页Video Engineering

摘　　要：介绍基于人工智能生成内容(Artificial Intelligence Generated Content,AIGC)的媒体内容跨模态理解系统的整体架构设计与实现。该系统旨在通过高效的多模态处理能力,支持对视频、音频、图像以及文本等多种形式媒体内容的理解与检索工作。系统采用大模型技术,将各种类型的多媒体数据转化为结构化的特征向量,并存储起来以备后续使用。这一设计不仅极大地提升了信息检索的效率,而且确保了检索结果的高度精准性,从而能够满足不同应用场景。This paper introduces the overall architecture design and implementation of a media Content cross-modal understanding system based on Artificial Intelligence Generated Content(AICC).The system is designed to support the understanding and retrieval of various forms of media such as video,audio,image and text through efficient multimodal processing capabilities.The system uses large model technology to transform various types of multimedia data into structured feature vectors and store them for future use.This design not only greatly improves the efficiency of information retrieval,but also ensures the high accuracy of the retrieval results,so as to meet different application scenarios.

关 键 词：内容理解 跨模态 检索 

分 类 号：TN931.1[电子电信—信号与信息处理]