Originally published at: https://boingboing.net/2018/06/25/adblocker-for-radio.html
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Actually, dynamic compression is used in practically all professional audio recording situations, not just ads and shitty pop songs.
AFAIK, there is no DSP algorithm that can detect a compressed signal (I’m pretty sure it’s impossible, but I could be wrong), but even if there were, I doubt it would help you separate the audio you want from the audio you don’t want.
ETA:
It appears the post has been amended to refer to “extreme waveform compression.” Thanks for reading my comment, Rob! The compression process has many parameters, so there is no one “extreme”-type of compression, but many. Unfortunately, all of those extremes have legitimate signal processing uses, and are not exclusively used by advertisers and shitty pop songs. So, I’m sorry to say, you probably wouldn’t be happy with the operation of your fantasy filter.
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If it works on pledge breaks, sold.
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I had a similar idea once, while waiting in a car dealership. The unstoppable TV was showing a commercial for a rival auto brand, and it occurred to me it would be simple engineering to detect commercials, filter them out and substitute in your own. Or P&G could offer a service to dentists that inserts toothpaste commercials and pay the dentists to run it.
As my Momma used to say, if I’m so smart why ain’t I rich?
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just pre-buffer a few minutes of whatever radio, audio or video stream you want and use a keystroke or click to jump 30 seconds when you want
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This.
First thing I do in the am before going to the bathroom, while the work comp is booting, is to start the stream on the tablet. If you don’t mind the times being off when discussed “on air” it’s a great way to avoid commercial breaks as well as skip songs you hate. ( I listen to a local morning show, and they periodically have music breaks. Like a lot of the stuff they play, but there are some artists that just rub me the wrong way, and bb4me’s trick lets me skip the umpteen billionth time I’ve heard something).
And I’d like to commission a study into why some songs start out good, and only get better with time/more listening like Toto’s “Africa” or say Duran Duran’s “Save a prayer”, but some that you may have liked in the beginning (ahem, Green Day’s “Boulevard of Broken Dreams”) are now so grating and painful to hear. Of course, likely specific to the listener, not likely the song itself. But if I could figure out some principal of universality, I’m going to release an album of “NOW THOSE ARE EARWORMS VOLUME 1!!!” and retire.
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Loudness wars are becoming more and more rare as many legit radio stations are employing loudness normalization to keep the listener from having to reach for the volume dial. TV and many streaming platforms are already completely loudness normalized.
That’s not the Cowboy Way now, is it? (Is now? Oh. Well. Got the pull request in for you then.) Just make the retrofit (and toggle) with the parameter salad of the month and give it a go. Or rather, now that the under-$10 IoT mcu market is all primed for edge ML, have you a go at both moving all the citation to the front (IT’S Magna Chakraborty and Amy Goodman FLYING CIRCUS) and making all the ads into dronecore except the ones with events affecting traffic or whatever. Then get offering modular radios in case it takes off. Or chain store stream foolery. Or arrange for a $8 cheap radio fixer to make all the shout-outs include names you really need to know.
?>Many streams are normalized.
Well, it doesn’t seem right on the Harpsichord Channel, and of course I’d interpreted it as public television having fired and/or shot all their actual broadcast engineers.
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I listen to CBC Radio and dom’t understand the problem.
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Is there a True Cyberpunk badge on this board? Cuz I think you’ve earned a few.
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I’ve been thinking for a while of training a program (tensorflow or the like) to just filter out any non-music sound from a radio stream. While the community radio stations I listen to don’t typically have many ads (more like non-obnoxious sponsorship announcements), I often just want the music, and none of the presenters talking or interviews. Surely it wouldn’t be that hard; just need to learn tensorflow…
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How fast are you? How dense? How chthonic?
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