Interesting, but it feels like the music is forever stuck in an into of some kind. I never quite get the feeling that it's building towards something.
Think that may be by design: > The goal of these experiments were to see if LSTM could learn a fixed chord structure while in parallel learning elements of a varying melody structure. It was easier to stick with a basic melody. Note that every 12-bar segment is unique; however, because only one or two bars are changed at a time, you may have to listen for a while to hear differences. We are currently working on a muc…
Composing Music with LSTM Recurrent Networks – Blues Improvisation (2002)
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Re: Composing Music with LSTM Recurrent Networks – Blues Improvisation (2002)
#12This is from 2002, right?
It is indeed - I'd suggest the title is modified to add year as it provides context for how long LSTMs have been established before their recent popularity boom. https://scholar.google.com/scholar?hl=en&q=A+First+Look+at+M...
Re: Composing Music with LSTM Recurrent Networks – Blues Improvisation (2002)
#13Author ( http://research.google.com/pubs/author39086.html ) of the paper here. I'm amused this is on Hacker News. The goal was to learn very long-timescale limit cycle behavior in a recurrent neural network. The chord changes are separated by many intervening melodic events (notes). As it turns out, even LSTM is pretty fragile when it comes to this. One problem is stability: if the network gets too perturbed, it can…
Re: Composing Music with LSTM Recurrent Networks – Blues Improvisation (2002)
#14Author ( http://research.google.com/pubs/author39086.html ) of the paper here. I'm amused this is on Hacker News. The goal was to learn very long-timescale limit cycle behavior in a recurrent neural network. The chord changes are separated by many intervening melodic events (notes). As it turns out, even LSTM is pretty fragile when it comes to this. One problem is stability: if the network gets too perturbed, it can…
Hi Douglas, I just finished my college and quite interested in RNNs and fascinated by their capability and potential. Should I go to graduate school to study it or I can play with it as a hobby. Do you have any suggestions?