This code is designed to transcribe an audio file into text using the Whisper speech recognition model from OpenAI. I mainly use it to create transcriptions of meetings with clients so I can format them into meeting minutes.
I used a Python virtual environment to install the dependencies, so I decided to leave a requirements file to make installation easier using pip. The document is requirements.txt.
To run the code, simply pass the path of an audio file (I have only tested it with .m4a files) as an argument.
python main.py [path]It's important to ensure that all Whisper dependencies (such as ffmpeg) are installed and to follow the recommendations in the repository.
The code does not download the model because an SSL verification is required to download it directly from OpenAI. Therefore, I preferred to download and install it manually. Just place the model in /home/$USER/.cache/whisper/ (I also suggest renaming it to the model name, such as "base", as the file usually comes with a name like "Whisper base", for example).
The transcription is saved in a folder named output.