ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM

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. 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. 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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-09
DOI
https://doi.org/10.5281/zenodo.20096303
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
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article

ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM

Dhruv Gonnade
Zenodo (CERN European Organization for Nuclear Research)
Generative Adversarial Networks and Image Synthesis
article

ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM

Dhruv Gonnade
article en

Abstract

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. 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. 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.

Zenodo (CERN European Organization for Nuclear Research)
Dr. Babasaheb Ambedkar Technological University (IN)
Quality Education
Openalex Percentile: Top 4%
Generative Adversarial Networks and Image Synthesis
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ANIMATOR – AI-POWERED TEXT-TO-VIDEO ANIMATION SYSTEM — Dhruv Gonnade · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS