It's not clear from the blog post how note durations are modeled, but the notes do appear to have different durations. Can you say more about this?
Extremely excited to share work I've been doing at OpenAI the past few months: MuseNet, a neural net music generator. It's been a huge team effort pulling this all together!https://twitter.com/OpenAI/status/1121457782312460288 …
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Great question! This is controlled by the volume of the notes. The model turns a note on with say a violin:v80:G token, and then turns it off later with a matching violin:v0:G token.
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I also played around with one model that only generated notes and then a second one that calculated the lengths and volumes, but I came back to using the on/off tokens.
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We've played with many such schemes too. I even tried adding common n-grams to the vocabulary (to shorten sequences) but the model had a hard time figuring those out.
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Yes, agreed the actual encoding matters a lot! I've also played around with bytepair encoding when it was piano only, but that got complicated once I added all the instruments, and allowed the piano to have many different volumes
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Yeah, for me the merged tokens didn't really end up corresponding to anything intuitive. Combining pitch and velocity makes more sense, though does conceal from the model that e.g. loud-C and quiet-C are actually the same note.
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Agreed. I played around with factorizing the embeddings to force it to commit to one set for the pitch and one for the volumes, but that didn't actually seem to help
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Oh, I did do a lot of data augmentation on the volumes, especially early on
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Very nice work. Please come give a talk to Magenta!
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Thanks, yes I'd love to connect - I'm a big fan of Magenta's work!
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"Researcher admits AI bias" ;) for the piano parts.
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It's funny I keep thinking back to this. Even tho my bias was benign (unless you count the few awful elevator-music generations :) it makes me realize how easy it is for bias to creep in. Not any big decision, just the million little choices what to focus on at a given moment.
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It creeps up on us I guess. I replied more in jest, based on your comment on Twitch - but you are right, our domain expertise can become our bias.
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Congrats! This is Awesome!
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Thanks!
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Hey Christine, this is so awesome. I've been wanting to work on something like this for a while. Woo! I actually make/write pop/EDM songs. Can I collab with you on one? I am most interested in AI that can generate chord progressions.
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Yes! I'm very excited about collaborations. Can you email musenet@openai.com with details? That'll go to me.
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Congrats!! Some samples are unbelievably good! It’s a shame that midi playback can’t depict well some musical features such as fast repeating notes and tremolo. I guess a possible next step could be to teach a model to use real instrument samples using midi as input.
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Thanks! Yes, I haven't focused on the midi->raw audio part at all yet, totally agree it's a big limitation.
@GoogleMagenta is doing some really cool work in this direction -
Well but the midi part is the real challenge, I would say. The raw audio is just final polishing
Thanks for suggesting @GoogleMagenta, I will take a look at it!
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