| _version_ | 1866901429916008448 |
|---|---|
| author | Gonnade, Dhruv |
| author_facet | Gonnade, Dhruv |
| contents | <p class="isSelectedEnd">This research paper presents “Animator”, an AI-powered text-to-video animation generation system designed to simplify and automate the process of creating animated videos from textual input. The proposed system integrates advanced artificial intelligence technologies including natural language processing, Stable Diffusion for image generation, AnimateDiff for animation synthesis, text-to-speech models for voice generation, and Whisper ASR for subtitle generation.</p> <p class="isSelectedEnd">The system follows a modular pipeline architecture consisting of input processing, script generation, scene structuring, visual generation, animation rendering, audio synthesis, subtitle synchronization, and final video rendering. The proposed approach reduces the complexity, cost, and technical expertise traditionally required for animation production.</p> <p>The generated results demonstrate that the system can efficiently create synchronized animated videos with minimal user effort, making it useful for applications in education, marketing, entertainment, and digital content creation.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20096303 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM Gonnade, Dhruv Artificial intelligence Computer vision Natural language processing Deep learning image generation Generative ai animation <p class="isSelectedEnd">This research paper presents “Animator”, an AI-powered text-to-video animation generation system designed to simplify and automate the process of creating animated videos from textual input. The proposed system integrates advanced artificial intelligence technologies including natural language processing, Stable Diffusion for image generation, AnimateDiff for animation synthesis, text-to-speech models for voice generation, and Whisper ASR for subtitle generation.</p> <p class="isSelectedEnd">The system follows a modular pipeline architecture consisting of input processing, script generation, scene structuring, visual generation, animation rendering, audio synthesis, subtitle synchronization, and final video rendering. The proposed approach reduces the complexity, cost, and technical expertise traditionally required for animation production.</p> <p>The generated results demonstrate that the system can efficiently create synchronized animated videos with minimal user effort, making it useful for applications in education, marketing, entertainment, and digital content creation.</p> |
| title | ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM |
| topic | Artificial intelligence Computer vision Natural language processing Deep learning image generation Generative ai animation |
| url | https://doi.org/10.5281/zenodo.20096303 |