This project aims to enhance the accessibility and engagement of English-language educational videos for Urdu-speaking students through advanced translation and lip reanimation techniques. The project includes translation of video content, synchronization of lip movements with translated audio, and personalized explanations for technical terms.
- Objective: Translated English-language educational videos into Urdu to improve comprehension for Urdu-speaking students.
- Technologies Used: OpenAI Whisper and Google Translate.
- Description: A machine learning model was developed to perform the translation, ensuring that students more comfortable with Urdu can fully engage with the instructional material.
- Objective: Enhanced the immersive learning experience by synchronizing video presenters' lip movements with translated Urdu audio.
- Technologies Used: Wav2Lip and LipGan.
- Description: Lip reanimation techniques were implemented to create a realistic illusion that the speaker is conversing in Urdu, bridging the language gap and creating a more engaging online learning environment.
- Objective: Tailored the learning experience within video content by leveraging Natural Language Processing (NLP) for generating explanations of technical terms.
- Technologies Used: Llama 2 model.
- Description: Personalized explanations for technical terms were generated using the Llama 2 model, enhancing the understanding of complex concepts.