摘要
Abstract
To address the issues of modal fragmentation,insufficient structural processing capabilities,and poor user interactivity in open-source intelligence systems,an intelligent information processing system integrating computer vision,natural language processing,and text-to-speech technologies has been proposed.Based on multi-source heterogeneous data,a complete closed-loop workflow was designed,covering data acquisition,preprocessing,deep modeling,intelligent decision-making,and user interaction feedback.The study focused on breakthroughs in key technologies such as cross-modal data fusion,structured intelligence content processing,voice broadcasting,and multimedia visualization.Experimental results showed that the system achieved excellent performance in key indicators such as intelligence extraction accuracy,response time,and user-interpretable feedback.The system is modular and scalable,making it suitable for applications in government security,financial risk control,and public opinion monitoring.关键词
开源情报/计算机视觉/自然语言处理/文本转语音/语音识别/多模态融合/大语言模型/人工智能Key words
open-source intelligence/computer vision/natural language processing/text-to-speech/automatic speech recognition/multimodal fusion/large language model/artificial intelligence分类
社会科学
