Breaking Down Language Barriers: Using AI and NLP to Automate Dubbing Process for Improved Accessibility and Inclusivity

Local Chapter Montreal, Canada Chapter

Coordinated byCanada ,

Mohamed Kandil

Status: Completed

Project Duration: 20 May 2023 - 15 Jul 2023

Open Source resources available from this project

Github Repository

Project background.

The challenge is to develop an AI-powered dubbing app that automatically dubs videos in different languages. The app should be able to detect speech in the original video and generate synchronized dubbing in the desired language using advanced machine learning and natural language processing techniques. The application will streamline the dubbing process, making it more accessible and cost-effective for various sectors, including education, entertainment, business, tourism, and news.

The problem.

Traditional dubbing methods are time-consuming, expensive, and often require a large team of professionals. The AI Dubbing App Challenge aims to provide an innovative solution that can streamline the dubbing process and make it more accessible and affordable.

The AI-powered dubbing application can cater to diverse applications, such as entertainment, education, documentaries, webinars, conferences, language learning, tourism, business, news, social media, and accessibility for blind people.

Project goals.

- Develop an AI-powered dubbing app that can detect speech in the original video and generate synchronized dubbing in the desired language. - Improve the accuracy and quality of the dubbing process using state-of-the-art machine learning and NLP techniques. - Provide an innovative and affordable solution for content creators and language learners. - Promote inclusivity and accessibility by designing the AI-powered dubbing application to cater to the needs of diverse users, including individuals with visual impairments and non-native speakers. - Contribute to the advancement of machine learning and NLP techniques by sharing the project's findings, challenges, and successes with the broader scientific and research communities.

Project plan.

  • Week 1

    Introduction and Planning

  • Week 2

    Data Collection

  • Week 3

    Prototype Development

  • Week 4

    Prototype Development

  • Week 5

    Prototype Refinement

  • Week 6

    Final Testing and Evaluation

  • Week 7

    Final Report and Presentation Preparation

  • Week 8

    Final Report and Presentation Preparation

Learning outcomes.

Participants will acquire expertise in advanced machine learning and NLP techniques, including speech recognition, language translation, and text-to-speech synthesis. Participants will gain practical experience in designing and implementing AI solutions addressing real-world issues in the entertainment, education, and other industries. Participants will enhance their collaboration, problem-solving, and creativity skills through team-based project development.

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