Testing live-time audio transcription with OpenAI Whisper on Raspberry PI 5

Introduction

This tutorial will guide you through the process of using OpenAI's Whisper for real-time audio transcription on a Raspberry Pi 5. We will cover everything from setting up your device to running tests with different AI models, making it a comprehensive resource for anyone interested in audio processing and transcription technology.

Step 1: Prepare Your Raspberry Pi 5

• Ensure your Raspberry Pi 5 is set up with the latest version of Raspberry Pi OS.
• Connect your microphone to the Raspberry Pi. You can use a USB microphone for better compatibility and audio quality.
• Update your system to ensure you have the latest packages:

  sudo apt update
  sudo apt upgrade
  

Step 2: Install Necessary Dependencies

• Install Python and Pip if they are not already installed:

  sudo apt install python3 python3-pip
  

• Install additional audio libraries:

  sudo apt install ffmpeg libsndfile1
  

• Install the Whisper library from OpenAI:

  pip install git+https://github.com/openai/whisper.git
  

Step 3: Test Audio Input

• Check your microphone setup by testing audio input. You can use the arecord command:

  arecord -l
  

• Use the following command to record a short audio clip:

  arecord -D plughw:1,0 -f cd test.wav
  

• Play back the recording to confirm that the microphone is working:

  aplay test.wav
  

Step 4: Run Whisper for Transcription

• Create a Python script to transcribe audio:

  import whisper
  
  model = whisper.load_model("base")  # You can choose different models like tiny, small, medium, or large
  result = model.transcribe("test.wav")
  print(result["text"])
  

• Run your script to see the transcription results:

  python3 your_script_name.py
  

Step 5: Experiment with Different Models

• Try different Whisper models for varying transcription accuracy and speed:
  • Use smaller models like tiny or small for faster performance with less accuracy.
  • Use larger models like medium or large for better accuracy but longer processing times.
• Adjust the model in your Python script by changing the model name in the load_model method.

Conclusion

In this tutorial, you learned how to set up OpenAI's Whisper for real-time audio transcription on a Raspberry Pi 5. You went through the steps of preparing your device, installing necessary dependencies, testing your audio input, and running transcription using different models.

Next steps could include experimenting with different audio inputs, integrating the transcription into other applications, or exploring more advanced features of the Whisper API. Happy transcribing!