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.
Detecting the ads directly would be hard. The real way to do this would be to mark segments of *non-*advertisement and then send the information necessary to identify them to the client so that it can scan through the downloaded audio file and remove anything that shouldn’t be there. The algorithm would still be pretty complicated, but feasible.
This makes sense.
So mark the segment where an ad starts, then the segment when the show goes on. The client catches the audio snippet which can then be moved to autoskip ads.
It should be possible to detect non-ads by downloading different versions of the audio file and checking which sections are identical, but you’d need some way of detecting transitions between sections.
If the ads use a voice actor who doesn’t talk on the podcast, maybe you could try to detect that.
Those are both solutions that only work sometimes and for the former, you have no way of knowing if it worked unless you actually listen to the result. Having to download the podcast twice is also rather undesirable.
This gets to the heart of the difficulty of this proposed project though. Thanks for going down this train of thought to all involved, very interesting. I had hoped to utilize a series of user contributed timestamps, but this would get more complicated depending on region, distributor, etc. This is a project I’ll be thinking about long term though (and if I really think I have a solid plan, I’ll seek legal advice last to ensure I have all my ducks in a row). Thanks for the advice.