• 3 Posts
  • 90 Comments
Joined 6 years ago
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Cake day: June 2nd, 2020

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  • I used yunohost for a bit and while it was easy setup, it wasn’t easy to troubleshoot weird errors because hardly anyone uses it.

    I’d recommend setting up:

    • debian with a desktop environment to start with
    • figure out how to ssh into it from your main machine and maybe how to use tmux
    • docker and how docker works
    • self-hosting services using docker

  • Unfortunately no, audio files are actually really dumb in that they’re basically just a file of 44100 (or 48000 or 96000 etc) amplitude numbers per second.

    So there’s nothing really to diff because it’s basically just a squiggly line, set of squiggly lines or, when compressed, a mathematical expression that when decompressed, recreates a squiggly line.

    You could isolate the dialog if you got ahold of a version with no dialog at all and then inverse the polarity of that and sum it with the original but it’s unlikely you’ll find a version without any vocals.

    Machine learning vocal isolation tools are probably going to be the best way to go about it as a DIY approach. Ultimate Vocal Remover 5 with the demucs 4 algo is great FOSS software to extract vocals and you could sum that with the original track and adjust the gain to get louder dialogue… it would be a lot of work though…



  • As an audio engineer, this suggestion makes my skin crawl.

    Don’t apply any extra compression to your files this, it will ruin them.

    Modern audio streaming services and good audio players use loudness normalization to achieve consistent playback loudness. The way they do this is by measuring the integrated loudness of each song and increasing or, in most cases, reducing the playback gain of the song to an arbitrary target (e.g. Spotify has chosen -14LUFS which is pretty quiet when you consider most pop music is mastered to somewhere between -10LUFS and -3LUFS).

    OP should just find a better audio player or figure out how to enable loudness normalization.