How to Build a Python Project that Summarizes Your Lectures

Learn how to build a Python app that lets you study faster by automatically summarizing lectures! We use Streamlit to build the app, and AssemblyAI to generate transcript summaries and highlights. This can be applied, e.g., to video lectures or recorded Zoom calls.

With Automatic Transcript Highlights, the AssemblyAI API can automatically detect important phrases and words in the transcription text.

Auto Chapters provides a "summary over time" for transcribed files. It works by first segmenting the audio data into logical "chapters" as the topic of conversation changes, and then provides an automatically generated summary for each "chapter" of content.

In this tutorial we combine both features in our app, so that we can easily jump to the important parts in the video and read through the summaries.

Watch here: