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Machine Learning / Generative Music?

Hi all, any insight into machine learning and music? I feel like technology has gotten that far, im just not sure where it is haha. I would love to take 500 of my songs, stem them out, have the computer learn them and then generate thousands of loops.

Comments

  • For the machine to learn, you'll need to define some criteria and rate your 500 songs in a useful way.
    Without that, it's not really machine learning but rather randomization based on your input material.

  • @rs2000 good point. still no idea where to start haha. im going to do some digging. I found something for M4L in ableton, but it just generates midi based off the midi you feed it. not quite the same thing

  • @rs2000 said:
    For the machine to learn, you'll need to define some criteria and rate your 500 songs in a useful way.
    Without that, it's not really machine learning but rather randomization based on your input material.

    Not necessarily. You could train a machine learning generative model based on the raw audio, for instance. @shinyisshiny if you feel like digging in, here is one post to get you started: https://wandb.ai/authors/openai-jukebox/reports/Experiments-With-OpenAI-Jukebox--VmlldzoxMzQwODg

  • @bleep said:

    @rs2000 said:
    For the machine to learn, you'll need to define some criteria and rate your 500 songs in a useful way.
    Without that, it's not really machine learning but rather randomization based on your input material.

    Not necessarily. You could train a machine learning generative model based on the raw audio, for instance. @shinyisshiny if you feel like digging in, here is one post to get you started: https://wandb.ai/authors/openai-jukebox/reports/Experiments-With-OpenAI-Jukebox--VmlldzoxMzQwODg

    That's an interesting demo, thanks for the link!
    Got any examples that sound more "musical" than the ones shown?

  • No experience, have just seen some blog posts. Looks like the JukeBox from OpenAI has some examples etc. Scroll down here for examples and a good explanation. Note to readers: these samples are generated from scratch by a model, it is no re-sampling going on here.
    https://openai.com/blog/jukebox/

    Takes a long time to train these things oneself, though.

  • @bleep said:
    No experience, have just seen some blog posts. Looks like the JukeBox from OpenAI has some examples etc. Scroll down here for examples and a good explanation. Note to readers: these samples are generated from scratch by a model, it is no re-sampling going on here.
    https://openai.com/blog/jukebox/

    Takes a long time to train these things oneself, though.

    This is fun!
    I wonder though if creating MIDI files based on different artists' compositions wouldn't be a better idea...

  • This brings up an interesting question about how Apple Music uses ML. I listen to my huge music library on random most of the time and notice how there are subtle similarities between consecutive songs—not always but often. For example, a percussive classical piece might be followed by a percussive jazz piece. No other similarity, just the sense of propulsion. Then the next song seems to forgo the ML—an A capella trio, say. Happens enough that I notice. Anyone else have that experience?

  • @rs2000 said:

    @bleep said:
    No experience, have just seen some blog posts. Looks like the JukeBox from OpenAI has some examples etc. Scroll down here for examples and a good explanation. Note to readers: these samples are generated from scratch by a model, it is no re-sampling going on here.
    https://openai.com/blog/jukebox/

    Takes a long time to train these things oneself, though.

    This is fun!
    I wonder though if creating MIDI files based on different artists' compositions wouldn't be a better idea...

    Absolutely! See the link to their earlier work ;)
    https://openai.com/blog/musenet/

    They did audio to see how the more challenging domain would behave.

    With Musenet you can prime the model with six notes of Chopin and ask it to continue in a pop style from there. Quite impressive stuff.

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