AI-Drafted Transcripts from the Empty Realm
Introducing RadioTranscriptor: A Revolutionary Tool for SDR Hobbyists
RadioTranscriptor, a homebrew Python script developed by [theckid], is making waves in the world of software-defined radio (SDR) hobbyists. This innovative tool goes beyond the basic listening and recording capabilities of traditional SDR software, offering a unique blend of SDR, voice activity detection (VAD), and deep learning.
At its core, RadioTranscriptor captures live audio from SDR devices at a rate of 48 kHz. But it's not just about listening - it's about understanding. The script employs real-time VAD to analyse the audio, identifying segments containing speech. To ensure compatibility with OpenAI’s Whisper model and for more efficient processing, RadioTranscriptor resamples the audio on the fly from 48 kHz to 16 kHz.
To maintain a smooth and contextual transcription experience, RadioTranscriptor keeps a rolling buffer of recent audio frames. Only the segments flagged by VAD as containing speech are sent to the Whisper model, minimising unnecessary computation. The transcriptions are then logged daily for easy review of previous signal activity.
For those seeking a more personalised experience, RadioTranscriptor's open-source codebase is customisable. Users can adjust threshold settings, swap models, or even add features like speaker detection. The tool also supports GPU processing with CUDA, offering faster deep learning inference when a suitable GPU is available.
This integration of SDR, VAD, and deep learning enables users to extract meaningful speech transcriptions from the seemingly chaotic world of radio signals efficiently and in near real time. RadioTranscriptor is lean, geeky, and designed for SDR hobbyists. It helps users hear 'the voice in the noise' without actively listening to it themselves.
With RadioTranscriptor, SDR hobbyists now have a powerful platform for artistic expression. The tool's codebase can be used to create artistic interpretations of its functionality, and with its open-source nature, users can create unique, customised versions of the tool to suit their specific needs and preferences.
[1] [theckid]. (2022). RadioTranscriptor: Real-time SDR transcription with voice activity detection and deep learning. GitHub. https://github.com/theckid/RadioTranscriptor
[2] OpenAI. (2021). Whisper: Large-scale audio transformer model. GitHub. https://github.com/openai/whisper
[1] RadioTranscriptor utilizes data-and-cloud-computing and artificial-intelligence technologies to process and transcribe audio from radio signals in near real time, revolutionizing the experience of SDR hobbyists.
[2] With its open-source codebase and integration of technology like artificial-intelligence and data-and-cloud-computing, RadioTranscriptor serves as a pioneering tool in the realm of software-defined radio (SDR) hobbyists, offering a new platform for creative expression.
