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You almost exactly described my process: podcast-dl > whisper > Gemini > ffmpeg > ftp > cheap web host
by xnx 1y ago
You almost exactly described my process: podcast-dl > whisper > Gemini > ffmpeg > ftp > cheap web host
- thomassmith65 1y agoIf you've gone through that much effort, you might as well turn it into a subscription service. It would be resource intensive, but some people would gladly pay through their nose to rid their podcasts of ads.
- xnx 1y agoI'd definitely like to make it easier to use and spread it more widely, but I can't directly distribute the edited (copyrighted) podcast files. Might share transcript markers of the text right before and after ad segments, which is like a slightly more complicated version of what SponsorBlock does.
- walthamstow 1y agoWhat's your prompt for Gemini like, does it include examples of ads? Assume you're using Flash for cost? I also have a setup like this, I transcribe with Whisper and send it to OpenAI 4o-mini to detect ads then clip those segments with pydub, but my prompt must be lacking because the success rate on detecting ads is maybe 60%
- xnx 1y agoMy Gemini Flash 2.0 prompt: "Below is the transcript of a podcast preceded by a line number. Reply with the line numbers that are likely to be from advertisements, promotions, commercials, sponsorships, or ending credits." I think it's better than 60%, but I should definitely set up some evals. I split the text by sentence, but was considering having the LLM try and put into paragraph (that might conceptually chunk commercial sentences together), but what I've got has been good enough for me. I wanted to switch to Flash 2.5, but it looks like they increased the price a lot. I think I could do a fair bit of ad identification just with text heuristics: "This podcast is sponsored/supported by...", etc.