Automate Meeting Notes with Python

In this tutorial, we learn how to build a web application that automatically generates meeting notes from an audio recording using Python and Streamlit. The app requires three main components: Streamlit for creating the user interface, Python for coding the backend logic, and AssemblyAI's Speech-to-Text API for transcribing and analyzing the audio file. The first step is to set up the structure of the Streamlit application, which includes uploading an audio file and playing it back. Next, we send the uploaded audio file to AssemblyAI for transcription and analysis. We use two different NLP capabilities of AssemblyAI: Topic Detection and Auto Chapters (Summarization). To connect to AssemblyAI, we need to set up headers with an auth_token obtained from their API. We then create a function to upload the audio file and start transcribing it. This function also returns a polling endpoint for checking the transcription status. After receiving the results from AssemblyAI, we display the main themes of the meeting using Streamlit's expander widget. We also show chapter summaries with their corresponding headlines and gist. To make the audio player jump to each chapter, we use Streamlit session states and callback functions. The final app allows users to upload an audio file, transcribe it, and view the meeting notes with chapters and themes highlighted.