RadioTranscriber: Real-Time Public Safety Radio Transcription with Whisper AI
Over in our new forums, user Nite has shared a new open-source project that he's created called RadioTranscriber, a real-time speech-to-text tool for public safety radio feeds using OpenAI’s Whisper large-v3 model. The idea is to take live scanner audio, such as authenticated streams from Broadcastify, and continuously turn it into readable text with minimal babysitting. The project grew out of earlier experiments with Radio Transcriptor, which we posted about back in June, but quickly evolved into a more robust, long-running setup with better audio conditioning and fewer of Whisper’s common hallucinations.
Under the hood, RadioTranscriber is a Python script that pulls in a live stream, cleans it up with filtering, normalization, and WebRTC VAD, then runs Whisper large-v3 with beam search for transcription. A set of custom “hallucination guards” strips out common junk text and replaces alert tones with simple markers, while daily log rotation and basic memory management let it run unattended for long periods, even on a modest CPU-only machine. Although it’s tuned to the author’s local dispatch style, the config and prompt are easy to adapt, and the full code is available on GitHub for anyone who wants to experiment or build on it.
