Watching our peers work for hours at a stretch to summarize our textbook content, lecture notes and lecture captures before exams, we provide a tool to perform that process instantly to help you revise better!

What it does

Summa takes inputs of audio or video files from lecture captures or tutoring sessions, and takes inputs of pdf files or direct text entry for either textbooks or lecture notes which it summarizes to produce a bitesize exam review guide.

How we built it

We used the AssemblyAI APIs to summarize content from video and audio files, while using PDFMiner and Spacy (Python libraries) to extract text from PDFs and summarize text respectively.

Challenges we ran into

While using APIs for the first time, we were quite confused about how to navigate the process of using queries to write our code. Moreover, while using PDFMiner and Spacy for the first time, we found it quite challenging to adapt to the methods that the code required from each of these libraries.

Accomplishments that we're proud of

We're proud of identifying a problem that most of our peers (including us) face, and attempting to solve that this weekend with our beginner coding knowledge!

What we learned

  • How to go about looking for a problem and ideating the solution
  • How to use APIs and queries efficiently
  • How to make the most of new libraries in Python
  • How to put everything together to present our project successfully

What's next for Summa

We hope to test it out for various subjects, ranging from STEM to humanities to languages, and hope that our classmates at our university and beyond can benefit from it!

Built With

Share this project: