Are there companies/projects that are working on cleaning up radio signals like that in real-time with digital signal processing ?
I used to work in the music industry, where there are many other real-time processing tools that can be applied to radio voice to increase clarity (eg: removing the static noise under speech, re-equalizing the limited bandwidth to increase perceptibility, de-reverberation etc..)
Considering such radio communications are often used in mission-critical scenarios, one would think clarity of speech would be a factor to consider.
There is software to do this. You can even configure your streaming / recording tool of choice to use that processed audio directly.
For the first couple of video courses I made my work flow was:
- Open REAPER (a software DAW with a business model like Sublime Text)
- Create and save a noise gate sample based on my specific room noise using its "ReaFIR" VST plugin until it was good
- Use a piece of software (ASIO Link Pro) to act as a virtual audio switch
- Open my video recording tool of choice (Camtasia)
- Configure Camtasia's microphone to be a virtual device that ASIO Link Pro created on my system
So now the end result is the audio being recorded live is already processed by REAPER and has no background noise. I also added in effects like a compressor and EQ too to offset my very thin microphone at the time. Totally seamless with no latency issues. You could do the same thing with OBS but OBS is even easier since you can directly use VST plugins so you don't even need REAPER or ASIO Link Pro running. You can download REAPER's VSTs separately.
Nowadays I just use hardware to do the same thing in real time so I don't need to think about it and I have flexibility in the recording tools I use, although the above approach works fine once you have it all configured. You would just open REAPER before your recording tool and it was ready to go.
Personally I would never go back to editing in post production for recording voices with a microphone. The amount of time the above saves is massive because it's all done on the fly with zero human intervention once it's set up. There's no complex import / export / import flow needed or fiddling with things for every recording.
Digital communication has a wholly different set of requirements than audio processing. With audio it is good enough to sound good, but digital communication has far more specific metrics of performance.
Digital communication is also far more structured, which makes it possible to implement a large number of techniques for improving signal quality.
Almost all digital communication systems would have something along: adaptive equalization, carrier tracking, symbol clock tracking, forward error correction, and many, many more techniques.
I agree that the technical requirements for transmission are very different than in a professional audio context. What I meant is that, once the signal has been acquired, there could be some additional processing to make it "sound better" (is: increase speech legibility), independently from the transport method.
I’ve only learned about this through my engineering studies, so I can only really recommend textbooks. I found Proakis’ Digital Communication quite good, but it doesn’t go very deep.
I don’t know of any online resources – but I’d love to have the time to write some signal processing for communication is fascinating and has a wide impact on everyday life.
Also wrt. implementations: I think GNU Radio might be a good place to look, but honestly the actual implementation of these algorithms is often very simple, it is the theory behind them that gets hairy.
I used to work in the music industry, where there are many other real-time processing tools that can be applied to radio voice to increase clarity (eg: removing the static noise under speech, re-equalizing the limited bandwidth to increase perceptibility, de-reverberation etc..)
Considering such radio communications are often used in mission-critical scenarios, one would think clarity of speech would be a factor to consider.