Let's build an interactive web app that can transcribe KZread videos in minutes! Streamlit is a great Python library that makes web development a piece of cake. And on top of Streamlit's powerful framework we will plug in Assembly AI's easy-to-use API to quickly upload and transcribe audio files.
Sign up for a free AssemblyAI API token here 👇
www.assemblyai.com/?...
In the first part of the tutorial we will create a project structure, install all necessary dependencies, create a base Streamlit app with which we can test our code and develop the Python function that starts the transcription process.
We will use three main libraries: Streamlit, KZread_dl and FFmpeg. These libraries will enable us to create a front-end for our project, download youtube videos and extract audio files from youtube videos respectively.
All the code in this tutorial is shared through a public Github repository. (github.com/misraturp/KZread-...)
This is all possible with only the free API token provided by Assembly AI. Sign up to get your own free API token here: www.assemblyai.com/?...
👩‍💻 Grab the code: github.com/misraturp/KZread-...
📥 Download FFmpeg: ffbinaries.com/downloads
✍️ See this tutorial in written format: www.assemblyai.com/blog/how-t...
00:00 Introduction
00:19 App overview
00:31 Get your own free API token
01:01 Let's get started!
01:25 Creating the project structure
02:35 Installing dependencies
05:26 Starting the Streamlit application
06:40 Setting up youtube_dl constants
07:50 Setting up the AssemblyAI API options
08:33 Getting the free API token
09:39 Extracting audio from the KZread video
12:38 Uploading the audio to AssemblyAI
13:15 Starting the transcription
15:22 Checking that the code works correctly
16:31 Like and subscribe!