AI Lip-syncing Web Application

Project Domain / Category

AI Web Application

Abstract / Introduction

In the era of digital content creation, the demand for high-quality videos has never been greater. One key aspect of video production is ensuring that the audio is perfectly synchronized with the lip movements of the characters on screen. However, manual lip syncing can be a time-consuming and labor-intensive process.

The objective of this project is to develop a web-based AI lip-sync application that revolutionizes the way videos are created and edited. This application will take a video (which needs lip syncing) and an audio/speech file as input. It will then use advanced deep learning techniques to analyze the audio and generate precise lip movements that match the audio's content and timing. By seamlessly syncing the audio with the video's lip movements, the application will significantly improve the overall quality and realism of the video content.

Functional Requirements:

            User Authentication: Users should be able to create accounts and log in to the application.

            Upload Video and Audio: Users should be able to upload video files that require lip-syncing and audio/speech files that will be lip-synced with the video.

            Lip Sync Processing: The application should use deep learning algorithms to analyze the audio and generate corresponding lip movements for the video.

            Preview and Edit: Users should be able to preview the lip-synced video and adjust, if necessary, before finalizing.

            Download Output: Users should be able to download the final lip-synced video for use in their projects.

            User Feedback: Provide a way for users to provide feedback on the lip-syncing results to improve the application's performance.

            Error Handling: The application should handle errors gracefully and provide meaningful error messages to users.

            Security: Ensure that user data is stored securely, and that the application is protected against unauthorized access.

Tools:

Development Environments / IDEs:

Backend Development: Python programming language will be used for the backend development. IDEs such as PyCharm or Visual Studio Code can be used for coding and debugging.

            Frontend Development: HTML, CSS, and JavaScript will be used for the frontend development. IDEs such as Visual Studio Code or Sublime Text can be used for coding and debugging.

Tools and Libraries:

            Deep Learning Framework: TensorFlow or PyTorch can be used for implementing the deep learning algorithms for lip-sync processing.

            Web Framework: Flask or Django can be used for developing the web application.

            Video Processing: OpenCV can be used for processing and manipulating videos.

            Audio Processing: Libraries like Librosa can be used for audio processing.

Supervisor:

Name: Sonia Salman

Email ID: sonia.salman@vu.edu.pk

Skype ID: sonia_salman