AI based Presentation Creator With Customized Audio Content Delivery
Project Overview
The document explores the innovative use of generative AI in education through an automated presentation creator that leverages machine learning and natural language processing to summarize research papers and generate corresponding slides. This tool includes a voice cloning feature that allows presentations to be delivered in the author's own voice, enhancing engagement and personalization. The system is particularly relevant in the context of the COVID-19 pandemic, as it addresses the increased need for efficient and effective presentation creation during the transition to online learning. By streamlining the process of developing presentations, the tool not only saves time for educators and students but also improves accessibility to educational content. The findings suggest that such generative AI applications can significantly enhance the learning experience by facilitating the dissemination of knowledge in a more engaging and efficient manner, ultimately contributing to better educational outcomes in a digital learning environment.
Key Applications
AI-based Presentation Creator with Customized Audio Content Delivery
Context: Educational institutions and workplaces adapting to online content delivery during the COVID-19 pandemic
Implementation: The system uses machine learning algorithms and NLP modules to automate the creation of presentation slides from structured documents (research papers) and employs voice cloning technology for audio delivery.
Outcomes: Reduced time for creating presentations and enhanced engagement through customized audio delivery.
Challenges: Challenges include the need for high-quality data for voice cloning and limitations in replicating specific voice styles and accents.
Implementation Barriers
Technical
The requirement for large and diverse datasets for effective training of voice cloning models, along with the complexity of integrating multiple machine learning models and ensuring they work seamlessly together.
Proposed Solutions: Utilizing techniques such as transfer learning and incorporating existing datasets to enhance model performance, and using frameworks like Streamlit and Google Colab to simplify the development and deployment process.
Project Team
Muvazima Mansoor
Researcher
Srikanth Chandar
Researcher
Ramamoorthy Srinath
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Muvazima Mansoor, Srikanth Chandar, Ramamoorthy Srinath
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai