Skip to main content

NeuroSDR — What it is (Hardware SDR First, AI Where It Helps)

NeuroSDR — What it is (hardware SDR first, AI where it helps)

Hello. This is KD8CEC.

NeuroSDR is a Windows software-defined radio receiver. The primary job is simple to state and hard to do well: take IQ from a real SDR, show a usable spectrum/waterfall, demodulate cleanly, and keep decoding plugins running while you still listen.

I publish release zips so most people never compile anything: NeuroSDR Releases.

NeuroSDR main window — local or discovered hardware appears under SOURCE; RX START runs the receiver.
NeuroSDR main window — local or discovered hardware appears under SOURCE; RX START runs the receiver.
How to read this series: NeuroSDR is a hardware SDR application. SDRplay, RTL-SDR, HackRF, Airspy / Airspy HF+, SoapySDR devices, and rtl_tcp are the main path. Virtual WebSDR / KiwiSDR / OpenWebRX sources exist as a convenience when you have no dongle or want a public remote site — they are secondary, not the product definition.

1. Why I built it this way

There are already good SDR programs. What I wanted on my desk was:

  1. Wide capture + many receivers at once — On something like an SDRplay RSP with several megahertz of instantaneous bandwidth, park MAIN on a shortwave broadcast or CW, while Sub VFOs keep decoding FT8 (or other AF plugins) on other dial frequencies inside that same window. That multi-receiver idea is one of the founding goals (see the RSP1 / Sub VFO video below).
  2. A full radio surface — Modes people actually use (AM/SAM/NFM/WFM/USB/LSB/CW/RAW/FreeDV, plus digital voice), dual audio outs, AFC, recording, memory/scan, SCENE layouts, satellite Doppler tracking.
  3. AI where audio is hard — Live captions/translation (NeuroCaption), RNNoise voice extraction, and speech-oriented scan helpers — without turning the app into a “demo that only works on YouTube.”

Design, coding, docs, and GitHub maintenance are driven by AI agents (Grok). I review, test on real radios, and ship the releases.

2. What is different from “another waterfall”

AreaWhat NeuroSDR does
Hardware firstNative paths for SDRplay, RTL-SDR, HackRF, Airspy, Airspy HF+, SoapySDR, rtl_tcp. Sample-rate / AGC / amp options live under SET → RF / Performance.
Sub VFOIndependent virtual receivers inside the capture window; AF plugins attach per VFO.
SCENENamed working sets: source, plugins, Sub VFOs, view, pop-outs — including a Satellite scene with Doppler-aware tracking.
NeuroCaptionAF plugin for speech-to-text + optional translation (local ONNX/Sherpa Whisper, Groq API, or self-hosted Whisper).
AF / IQ pluginsFT8/FT4, CEC CW, SSTV, RTTY, weather fax, Kiwi helpers, digital-voice bridges, ADS-B-style IQ paths, and more as instances.
AF hygieneRNNoise blend, AF bandpass, active CW filter, dual OUT1/OUT2 (e.g. speakers + VB-CABLE → WSJT-X).
Digital voiceDMR / D-STAR / C4FM via embedded DSD-FME path with dedicated feed AGC/volume.
Optional remote sourcesVirtual WebSDR / KiwiSDR / OpenWebRX when you want Internet RX without a dongle.
Optional web remoteBrowser/phone UI when enabled in SET → General (video for this path is still forthcoming).

3. AI captions (NeuroCaption) — real feature, not a sticker

NeuroCaption is an AF plugin. It listens to demodulated audio from MAIN or a Sub VFO. You pick an engine in Caption SETUP:

  • Local ONNX (Sherpa Whisper INT8 Tiny/Base/Small) — offline
  • Groq API — fast cloud Whisper when you have a key
  • Self-hosted Whisper — your own GPU/server

Optional MyMemory translation puts foreign shortwave speech into a language you can skim while still hearing the RF.

YouTube: AF plugins & caption system — 03:36
YouTube: Local ONNX engine — 04:07
YouTube: Groq API setup — 09:12
YouTube: Self-hosted Whisper — 12:16

4. About Virtual WebSDR / Kiwi (secondary)

Episode #2 on YouTube walks Kiwi/WebSDR for people with no hardware yet. That path is useful for travel, apartment antennas, or trying captions on HF overnight — but it is not why the Sub VFO / wide-band FT8 design exists. Wide simultaneous decode needs hardware instantaneous bandwidth.

Series on hamskey.com
  1. This post — concept (hardware first)
  2. Download + hardware install (RTL-SDR / Zadig, SDRplay API, …)
  3. Basic operation manual
  4. NeuroCaption & AF plugins
  5. Advanced: Sub VFO / FT8 / satellite / digital voice / Smart Record / web remote

NeuroSDR — KD8CEC · Blog: https://www.hamskey.com · Downloads: GitHub Releases · Source: github.com/phdlee/NeuroSDR

Comments

Popular posts from this blog

Introduction to UV-K5 HF 0.5 (Fullband receive version)

 Introduction to UV-K5 HF 0.5 (Fullband receive version) This is an introduction to UV-K5 HF full-band reception firmware 0.4HF using SI4732-A10. This version is released separately from the existing UV-K5 CEC firmware version. because space is needed to store a large PATCH file to use SI4732-A10's SSB. This article only describes the features newly added in Version 0.5. Please check the links below for full features. How to modify your hardware http://www.hamskey.com/2024/02/uv-k5s-hf-full-band-reception-lsb-usb.html Version 0.3HF (Most feature descriptions are provided) http://www.hamskey.com/2024/02/introduction-to-uv-k5-hf-fullband.html Version 0.41HF (Description of Band plan function and Dual RX function) http://www.hamskey.com/2024/03/introduction-to-uv-k5-hf-fullband.html

C-BOARD (DSP-Board) for UV-K5 (Updated June 9, 2024)

  C-BOARD for UV-K5 I created an externally mountable DSP-Board to process digital signals from UV-K5. DSP-Board was named C-Board. C-Board is divided into versions ranging from the simplest version to one that can be equipped with GPS.

Release DVPI Version 1.03 (scirpt update)

 Release DVPI Version 1.03 There have been some changes to the DMR node recently. This version changes only those related to the recently changed DMR node. If you normally use Version 1.0 or Version 0.95, no upgrade is required. DVPi uses the USRP Client protocol.  When you install and use DVSwitch, you must read and comply with the license that appears. The user is responsible for the license for the use of DVPi.