this post was submitted on 05 Apr 2024
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Asklemmy

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I'm part of a small group of Jr Self Taught Web Developers who were recently brainstorming ideas for a Group Project App we could put together and actually create a user base.

I offered up the suggestion of a podcast application which would have the major feature of being akin to YouTube Sponsor Block, but specifically for podcast episodes.

Essentially, a user contributed database of timestamps for podcast episodes where the mention of cutting to sponsored ads or mentions of sponsorships would be marked so they could be edited out of the episode and then the user could also download said episode where ads are cut out of the final audio file.

My idea was shot down due to fears of possibly infringing on copyright and we ended up with going with another idea. I'm certainly not upset, and am actually excited with the project idea we did choose, but it did get me wondering about whether this idea actually could have legal implications.

I know specifically with YouTube there appears to be a sort of legal loophole that prevents Google from suing projects like invidious, yt-dlp, and YouTube Sponsor Block, but am unaware of the specific details as to how this works.

Thusly, I just wanted to ask if anyone has any insights into whether this project idea would incur any legal infractions from the likes of IheartRadio and other media platforms?

To be clear, I'm not seeking legal advice here, and I'll be taking any responses with a grain of salt, but I just wanted to see if anyone knows anything on this subject and the legal concerns raised.

I very much dislike being advertised to and podcasts are one of the last bastions of media where advertisements still come up regularly and I'd love to make this application for those who are frustrated with how often they have to skip through sponsor mentions.

Thanks in advance.

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[โ€“] [email protected] 11 points 7 months ago (1 children)

You definitely would have legal issues redistributing the ad-free version.

Sponsor block works partly because it simply automates something the user is already allowed to do - it's legally very safe. No modification or distribution of the source file is necessary, only some metadata.

It's an approach that works against the one-off sponsorships read by the actual performers, but isn't effective against ads dynamically inserted by the download server.

One option could be to crowdsource a database of signatures of audio ads, Shazam style. This could then be used by software controlled by the user (c.f. SB browser extension) to detect the ads and skip them, or have the software cut the ads out of files the user had legitimately downloaded, regardless of which podcast or where the ads appear.

Sponsorships by the actual content producers could then be handled in the same way as SB: check the podcast ID and total track length is right (to ensure no ads were missed) then flag and skip certain timestamps.

[โ€“] [email protected] 0 points 7 months ago (1 children)

One option could be to crowdsource a database of signatures of audio ads, Shazam style. This could then be used by software controlled by the user (c.f. SB browser extension) to detect the ads and skip them, or have the software cut the ads out of files the user had legitimately downloaded, regardless of which podcast or where the ads appear.

That is one of the more unique ideas presented thus far. The other similar approach would be utilizing a trained AI model that would recognize advertisements and sponsor mentions. I'm not exactly sure how Shazam works, but that might be something to research in figuring out how best to approach this. Thanks.

[โ€“] [email protected] 1 points 7 months ago (1 children)

Yeah, I have no idea either, but it's been around for more than a decade so it should be fairly easy to find a library that duplicates it.

I would be wary of AI-based solutions. There's a risk of it picking up e.g. satirical/spoof sponsorships as actual ads, and perhaps not detecting unusual ads.

I'm slightly terrified of the day someone starts getting AI to reword and read out individual ads for each stream.

[โ€“] [email protected] 0 points 7 months ago

Perhaps that would be a good first step then. Figure out how Shazam works, then create a standalone application that catalogues and recognizes the audio of advertisements. An obvious name for such an app would be along the lines of "IsAnAd?". Then hook that standalone application up to a podcast aggregation client and use the timestamps of that to create the desired sponsor block functionality.

Thanks again. Just hashing this out with others like yourself has been super helpful.