Probability Multivalued Linguistic Neutrosophic Sets for Quality Evaluation of Digital Media Content Creation and Editing with Computer Assistance - Wen Li; Mengna Guo; Tian Tian (Neutrosophic Sets and Systems)
The use of computer-assisted tools and artificial intelligence (AI) has drastically changed the content generation and editing processes in the quickly changing world of digital media. by emphasis on usability, performance, creativity support, and automation capabilities, this research performs a thorough quality review of digital media content creation and editing systems augmented by AI. Six popular computer-assisted media tools, such as Adobe Premiere Pro with AI features, Final Cut Pro, and newer platforms like Descript and Runway ML, were evaluated using eight essential criteria, which ranged from editing effectiveness and aesthetics to user interface design and conformity to industry standards. Based on feature benchmarking and expert comments, a neutrosophic assessment methodology was used to assess each tool's performance. We use Probability Multivalued Linguistic Neutrosophic Sets to solve uncertainty information. The results show clear benefits and trade-offs amongst the platforms, providing information about how well-suited they are for various production and creative situations. This research helps educators and media workers choose the best tools for producing digital material that is scalable, effective, and of high quality.