A tool to convert spoken audio into accurate transcriptions and translations, using Whisper.
You need to create a virtual env and install the packages listed in requirements.txt. You can then run Jupyter Notebooks in VS Code.
Follow these steps: How to Work with Python Virtual Environments, Jupyter Notebooks and VS Code.
You need to create a .env file with your OPENAI_API_KEY.
For the CLI, we followed these steps.
Open Whisper Basics.ipynb.
To run the CLI:
cd 10-whisper-transcription-tool/local-whisper
python3 -m venv venv
source venv/bin/activate
pip3 install
You will need ffmpeg.
Then, you can run:
whisper "testing.wav" --model small --language English
- providing a prompt to Whisper.
- translating audio with Whisper.
- transcribing non-English audio.
- running the Whisper model locally.
- running Whisper in the command line.
Based on Mastering OpenAI Python APIs: Unleash the Power of GPT4 by Colt Steele (2023).