A Survey on Voice Cloning and Automated Video Dubbing Systems

In the context of today's interconnected world, where multilingual interactions are commonplace, the need for effective cross-language communication solutions is paramount. This survey explores innovative approaches to multilingual video dubbing, focusing on the integration of voice cloning and neural machine translation techniques for translating and dubbing videos across different languages while maintaining the authenticity of the original speaker's voice and ensuring seamless lip movement with the source video. Various advanced techniques, including voice cloning, speech emotion recognition, speech-to-lip synchronization, and neural machine translation, are employed in the examined literature. These techniques collectively aim to identify the source language, translate the content, and synthesize the speaker's voice in the target language that is synchronised with the source video. This survey also delves into the challenges associated with cross-language voice cloning and linguistic translation, exploring the collaborative potential of these technologies within the realm of video dubbing. The overarching goal is to contribute to the accessibility of multimedia content on a global scale, enabling viewers to enjoy videos in their preferred language without compromising the identity of the original speaker. Through comparative analyses of various algorithms, the effectiveness of these approaches in achieving high-quality, linguistically accurate, and emotionally resonant multilingual video dubbing is analyzed.