What is Whisper?

Whisper AI is an innovative machine learning model that is revolutionizing the way we process audio and speech.

This is a major OpenAI innovation in speech recognition and automatic transcription. This revolutionary model is designed to extract textual information from audio files, improving transcription efficiency. Whisper AI adapts to a variety of languages and dialects, making it a versatile tool for many applications.

How to extract text quickly (and for free) with Whisper?

To quickly extract text from an audio or video file using Google Colaboratory and Whisper, follow these steps:

  1. Access Google Colaboratory:
    • From your Google Drive account, install the Colaboratory extension
  2. Import the necessary libraries:
    • import the libraries required to use Whisper using the following code: !pip install git+https://github.com/openai/whisper.git !sudo apt update && sudo apt install ffmpeg
  3. Download your file and place it in the left panel
  4. Transcribe audio or video file:
    • Use the Whisper model to transcribe your audio or video file into text: !whisper "file_name.mp3" --model medium
    • Be sure to customize the path to your audio or video file and adapt the code to your specific needs.
  5. Execute code:
    • Click “Execute” to run each cell of code, making sure to load the desired audio or video file.

That’s it! You’ve now extracted text from your audio or video file using Google Colaboratory and Whisper.

To go further and learn more about whisper, visit the Open AI website: https://platform.openai.com/docs/guides/speech-to-text

What are the advantages of using audio transcription?

  • Optimization for SEO: It makes content indexable by search engines, improving online visibility.
  • Enhanced comprehension: Listeners can read at the same time, facilitating comprehension, especially for complex subjects.
  • Pedagogical support: Useful in education and training for better understanding.
  • Time and cost savings: Automatic transcription solutions, such as Whisper, save time and money compared to manual transcription.