Build Your Own Local Speech-to-Text System with Python and Whisper

Tired of the privacy risks of uploading sensitive audio to cloud transcription services? This post shows you how to build a local speech-to-text system using Python and OpenAI's Whisper model. Transcribe your audio files in under 10 minutes with 96% accuracy—completely free and processed locally on your laptop. The tutorial covers setting up FFmpeg, your Python environment, using the Whisper model, batch processing, creating SRT subtitles, and troubleshooting common issues. An alternative method using the `speech_recognition` library is also provided.