Audio Video Dubbing System

Abstract: With the rapid growth of digital media, the demand for multilingual audio video content has increased significantly. Traditional dubbing techniques are time consuming, costly, and require extensive human effort. This paper presents an AI based audio video dubbing system that automatically converts spoken content from one language to another while preserving the original speaker voice characteristics and synchronizing with the video. The proposed system integrates speech to text conver- sion, neural machine translation, and text to speech synthesis to generate natural and realistic dubbed audio. Voice cloning techniques are used to maintain speaker identity across different languages. Additionally, audio alignment is applied to ensure smooth synchronization between the generated speech and the video stream. The system aims to provide an efficient and scalable solution for content localization in applications such as education, entertainment, and online media platforms. Experimental results demonstrate that the proposed approach significantly reduces manual effort while maintaining acceptable audio quality and intelligibility.

Keywords: Audio video dubbing, voice cloning, speech synthesis, machine learning, multilingual translation, lip synchro- nization