AI Based Video Synthesis from Text

Recent advancements in artificial intelligence have enabled the development of systems capable of generating mul-timedia content directly from textual descriptions. Text-to-video generation is an emerging research area that aims to automati-cally create video sequences based on natural language prompts. However, most existing approaches require large training datasets and high computational resources. This paper proposes a zero-shot text-to-video generation sys-tem that converts textual prompts into short video sequences using generative models. The proposed system integrates natural language processing techniques with generative video synthesis to generate visual frames corresponding to the input description. These frames are then combined to produce the final video output. The system provides an interactive interface where users can input descriptive prompts, and the model generates correspond-ing video sequences. Experimental evaluation shows that the system can generate videos for various prompts with reasonable visual quality. The proposed approach reduces the dependency on large training datasets and demonstrates the potential of zero-shot generative models for automated multimedia content creation.