Speech-to-Speech Translation with Automated Lip-Synced Video Using Deepfake and TTS

Abstract

In today’s interconnected world, video content dominates communication, entertainment, and education, but language barriers often limit its accessibility. This project introduces a web application that seamlessly translates videos into a target language, enhancing inclusivity and cultural exchange. Using advanced AI technologies, it aligns translated audio with video through precise lip-syncing and facial expression adjustments, delivering an immersive and authentic user experience. At the core of this solution are generative adversarial networks (GANs) and deepfake technologies, which ensure high-quality translations and realistic synchronization of audio-visual elements. Developed with React, the application offers a responsive, scalable, and user-friendly interface optimized for computationally intensive tasks. Key challenges, such as audio-visual synchronization and contextual translation accuracy, were addressed to maintain video quality. This project demonstrates the potential of AI-driven multimedia applications in education, entertainment, and content localization. By bridging language gaps, it fosters cross-cultural collaboration and redefines interactions with multilingual video content.