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How I use Pinchflat/Sponsorblock to avoid podcast ads (github.com)

submitted 1 week ago* (last edited 1 week ago) by [email protected] to c/[email protected]

21 comments fedilink hide all child comments

I listen to a lot of podcasts. I spend a pile of time where I need something to distract me and keep me awake, and I also just like podcasts. But there's a lot of podcasts, especially from sources like IHeartRadio, that have scads of annoying ads (mainly for other podcasts, which seems weird, but OK).

I had gotten to the point where subscriptions like Behind the Bastards just weren't worth listening to because the ads went on for like 5 minutes. I had to come up with something or drop them.

Enter Pinchflat. You can create a "Podcast" media source profile that's audio-only, and respects Sponsorblock. If you have a podcast that has a Youtube channel, you can pretty much eliminate ads this way. And Pinchflat makes an RSS feed that you can subscribe to in your favorite app like Antennapod to consume that feed. One thing I like to add to the Media Profile is to redownload after a day or two so it updates the Sponsorblock info that might not have existed if Pinchflat grabs the episode when it's very fresh.

Links:

Pinchflat Docker compose setup

Podcast RSS feeds (Ignore the reverse proxy if you already use an always-on VPN like Wireguard/tailscale or download your episodes while on your LAN)

The heroes at Sponsorblock and the other heroes that contribute timeblock entries

Donate on behalf of Pinchflat to Zakkarry, a collaborator that the developer of Pinchflat has identified as a good donation target, as well as the EFF.

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[–] [email protected] 12 points 1 week ago (2 children)

But there’s a lot of podcasts, especially from sources like IHeartRadio, that have scads of annoying ads

And they're so repetitive. And each block is the same length if I'm not mistaken. This could even be automated - not relying on human input - or at least half-automated.

[–] [email protected] 1 points 6 days ago

I've had a pipeline in mind for exactly this purpose that I want to build when I get around to it:

Download the audio file from RSS feed
Self hosted AI transcription model (with output that includes timestamps)
Self hosted LLM to recognise ad sections and return the start and end timestamps as json
ffmpeg to slice those timestamps out and stitch the rest back together

In theory, this should be able to remove ad and sponsor sections of any length completely automatically and there's nothing to stop it working on videos too

[–] [email protected] 4 points 1 week ago (2 children)

It should be doable to so some audio analysis of the episodes. They "always" (I am sure some forget every now and then), have an outro and intro around the ad block. With a clearly defined jingle per podcast. You should be able to make a program that analyses the audio and listens for that block and cuts it out for you.

[–] [email protected] 1 points 1 week ago (1 children)

I had found one that used Whisper to convert the podcast to text and then ran it through an AI to find the ad text, but I couldn't get it to work. I had considered building something myself and was about halfway through that when I found this method. It does the job better than I think an AI would considering it's crowdsourced for the ad identification.

[–] [email protected] 2 points 1 week ago

This is exactly the route I've been begging for for years now. It seriously should be doable.

[–] [email protected] 1 points 1 week ago

Yep. Certain patterns are easily recognizable even by machines. One could have a relatively simple "IHeartRadio algorithm" that should work 99% of the time (esp. with Ed Zitron who brackets the blocks with that insane guitar riff).

Hell, I could even write that with ffmpeg and a shell script.

OK I'm being arrogant now, but not wrong.