Our inspiration sparked from observing the arduous process of traditional note-taking during lectures or sitting through hours of video recordings or PPTs. We were motivated to harness AI technology to streamline this task, empowering students to grasp information more efficiently and effectively.
Lecture Summarizer utilizes advanced AI algorithms to automatically generate concise summaries of lectures. We can either upload a video, pdf or both and it captures key points, highlights, and essential concepts, providing users with a comprehensive overview of the material covered.
We built Lecture Summarizer using a combination of natural language processing (NLP) techniques, machine learning algorithms, and speech recognition technology. We used Speech Recognition to convert video to text and Optical Character Recognition to extract text from pdfs.
One of the main challenges we ran into was computation power needed for converting video to text.
We're proud to have developed a robust and user-friendly platform that significantly enhances the learning experience for students. Seeing our AI accurately distill complex lectures into digestible summaries has been immensely rewarding.
Through the development process, we gained invaluable insights into the capabilities and limitations of AI in Software Development and educational technology. We also deepened our understanding of NLP, machine learning, and speech recognition methodologies.
In the future, we envision expanding Lecture Summarizer's capabilities to support additional languages, enhance its summarization accuracy through continuous learning, and integrate features for personalized learning experiences. We aim to forge partnerships with educational institutions to integrate Lecture Summarizer into their learning environments, ultimately revolutionizing how students engage with academic content.