Neural Networks Meet SDR: Building Your Own Speech Recognition in GNU Radio
The author shares their experience integrating the Whisper.cpp neural network into GnuRadio for speech recognition. The article covers building a custom GnuRadio block, adding it to a voice recorder and an FM receiver, and walks through examples with explanations.
AI-processed from Habr AI; edited by Hamidun News
Amateur radio and software-defined radio (SDR) development keep producing interesting new possibilities. One of them is pairing modern neural networks with signal processing and analysis. In this article, we look at how to combine GnuRadio, a powerful platform for building SDR systems, with the Whisper.cpp neural network for speech recognition.
Before getting to the integration itself, we need a quick tour of GnuRadio basics. We start with introductory lab exercises that explore generators and filters, as well as amplitude and frequency modulation. These help clarify what the platform can do and how signal processing works. Next, we build a simple voice recorder that saves audio in WAV format. This project serves as the starting point for everything that follows.
The main goal of the article is to build a custom GnuRadio block that performs speech recognition using the Whisper.cpp neural network. Whisper is a modern neural network developed by OpenAI that delivers impressive speech recognition results. Whisper.cpp is a C++ port of Whisper, optimized to run on a range of platforms, including embedded systems. With Whisper.cpp, we can run speech recognition locally, without sending data to a remote server.
Once the speech recognition block is ready, we integrate it into our voice recorder, so it can not only record audio but also automatically transcribe it into text. We also add the block to an FM receiver to recognize speech transmitted over the air. This opens up plenty of options for monitoring the airwaves and analyzing what gets broadcast.
Bringing neural networks into SDR systems opens new directions for signal processing and analysis. Speech recognition is just one example. Neural networks can be used for signal classification, anomaly detection, improving communication quality, and many other tasks. This makes it possible to build smarter, more efficient SDR systems.
In conclusion, integrating neural networks such as Whisper.cpp into GnuRadio is a promising direction for SDR technology. It enables powerful, flexible systems for signal processing and analysis, and gives radio amateurs, researchers, and developers new possibilities.
- Nov 1, 2026Local models lose to Opus and Codex: 0.21 on a MacBook versus 1.00 for Codex
- Nov 1, 2026Kimi scores 96.2% on a 1C database analytics test and emerges as a fallback if Claude access is blocked
- Nov 1, 2026OpenAI Rewrites GPT Behavior Rules: Five Values and a Chain of Command
- Nov 1, 2026Google admits AI Mode cuts search revenue, shares fall 15%
Test Frontier LLMs & Autonomous Agents in One Workspace
Run Claude Opus 5.5, GPT-6, Gemini 3.1, and DeepSeek side-by-side in Nomad AI (nomadnet.ai) — unified model routing, deep research, and multimodal workflows under one subscription.
The AI world, distilled — once a week
Seven stories that actually mattered, hand-picked. No noise, no reposts, no press releases.
Done! Check your inbox for a confirmation.