Podcast Summarizer is a Python application that utilizes the AssemblyAI API to summarize podcasts. It allows users to input an episode ID and generates a summary of the podcast episode, making it easier for listeners to quickly grasp the key points discussed in the episode.
The motivation behind this project stems from the creator's personal experience of listening to podcasts during long commutes. With lengthy podcast episodes and a busy schedule, it can be challenging to retain all the information conveyed in each episode. Additionally, keeping up with the frequent release schedule of some podcasts becomes daunting. Therefore, Podcast Summarizer aims to address these issues by providing concise summaries of podcast episodes for efficient consumption and easy reference.
Features
- Podcast Episode Summarization: Users can input the episode ID of a podcast episode, and the application will generate a summary of the episode's content.
- Chapter-wise Summaries: The application provides chapter-wise summaries, allowing users to navigate through different sections of the podcast episode and focus on specific topics of interest.
- Visual Representation: Podcast Summarizer displays the podcast's title, episode title, and thumbnail image for better context and recognition.
- User-Friendly Interface: The application utilizes Streamlit for a simple and intuitive user interface, making it easy for users to interact with and obtain podcast summaries.