5 ms·

Collective improvisation is the core of jazz's identity, more so than any of its other defining traits (swing, syncopation, blues-derived harmony, etc). Genera

Collective improvisation is the core of jazz's identity, more so than any of its other defining traits (swing, syncopation, blues-derived harmony, etc). Generating random patterns that sound jazz-ish is interesting, but until multiple generators can react to what the other is doing in real time (or to a human participant), it isn't exactly jazz. I'd equate it to a basketball playing robot. Teaching it to shoot free throws is interesting, but doesn't really take a step towards approximating what basketball is. Can it call for picks, lead passes to cutting teammates, box out for rebounds, force bad shots, etc?

Balgair 11y ago
Well, given enough time and resources, then yes, the b-ball-bot could, and probably better than a human could. I know this is a cop-out answer, but look at the DeepMind Go games. The computer beat a top 100 (I don't know the rankings, actually) Go player, something that was thought of as nearly impossible in this decade. The most interesting thing was if you read the commentary on the matches. The announcers were mystified by the computer's moves. 'Alien' comes up a lot in describing the play-style. Us humans can't play Go and evaluate each stone in the game. We have to 'chunk' the game. Exp: These 3 stones are a 'wall' or a 'platoon', this stone is 'hot' and can take your stones, this stone is 'down' and will be used in 3 turns, etc. The computer doesn't have to do that chunking, each stone is evaluated individually. As such, the play-style was totally foreign to people. It did things no player had tried or, importantly, could have thought of given the limits of our brains having to 'chunk' the information. I would predict that a b-ball-bot would play the same way, in totally strange ways that a human can't think of. Exp: Calculating a reasonably high probability that the ball will bounce off your nose and go into the left hand of it's team-mate, throwing the ball as hard as it can at it's own head to make a shot, not trying to get past just 1 opponent but the entire team's right thighs 57 seconds from now, etc. Similarly with jazz, the computer is a dumb machine that will just do strange things because humans have to 'chunk'. In music, we play in chords and notes and with rhythm and timing. The computer can evaluate the whole song, and every other song at the same time and can borrow from all those. You and I can pull in the feelings of loss of a child, or the joy of strawberry ice-cream bars in a Memphis summer, things a computer will never. But we cannot pull in the obscure Tuvan throat singing techno-remixes on Youtube , the Afro-Thai heavy metal Vimeo channels, or the terrible pre-teen angst poems set to crappy guitar, etc, all at once. It can only see what you feed it, but you can feed it the life-outputted-into-music of billions of humans with live updates. The computer will know more. But music is emotional and about feelings. The feel of music is most important to us. And I think that a human songwriter is therefore essential, one that cares and puts effort into the work. It connects us, and that is what is important, not the sounds.
- cdr 11y ago
  > But music is emotional and about feelings. The feel of music is most important to us. And I think that a human songwriter is therefore essential, one that cares and puts effort into the work. It connects us, and that is what is important, not the sounds. Children can play music very emotionally (or rather, in a way that adults associate with emotional) without having any experience of or real comprehension of the emotions. Imitation and training is sufficient to be convincing. A program doesn't need to experience emotion, only know that certain characteristics of the sound are associated with certain emotions.
mjn 11y ago
There's a little work on that part of jazz too, though not much. My undergrad supervisor built a solo-trading jazz system about 15 years ago for her PhD thesis. Solo trading isn't the full extent of jazz improvisation, but is at least getting at one of the collaborative parts of jazz. It's now slightly dated, but I think still good work, and could probably sound a lot better if the same basic approach was taken but updated with today's hardware and algorithms. Thesis: http://reports-archive.adm.cs.cmu.edu/anon/anon/2001/abstracts/01-138.html http://reports-archive.adm.cs.cmu.edu/anon/anon/2001/abstrac... A conference paper: http://www.aaai.org/Papers/AAAI/2000/AAAI00-100.pdf http://www.aaai.org/Papers/AAAI/2000/AAAI00-100.pdf
rryan 11y ago
> Generating random patterns that sound jazz-ish is interesting, but until multiple generators can react to what the other is doing in real time (or to a human participant), it isn't exactly jazz. For an arbitrarily complex network, it could internally develop independent generators that react to each other. However, the likelihood of common optimization strategies used for training RNNs (back-propagation through time, foveation/attention, etc.) developing a network like this is probably quite small. It would be possible for a network designer to come up with a structure (as Hochreiter did with LSTMs) that lends itself to this sort of structure but then you're baking in assumptions about how humans accomplish a task (which comes with trade-offs).

Balgair 11y ago

Well, given enough time and resources, then yes, the b-ball-bot could, and probably better than a human could. I know this is a cop-out answer, but look at the DeepMind Go games. The computer beat a top 100 (I don't know the rankings, actually) Go player, something that was thought of as nearly impossible in this decade. The most interesting thing was if you read the commentary on the matches. The announcers were mystified by the computer's moves. 'Alien' comes up a lot in describing the play-style. Us humans can't play Go and evaluate each stone in the game. We have to 'chunk' the game. Exp: These 3 stones are a 'wall' or a 'platoon', this stone is 'hot' and can take your stones, this stone is 'down' and will be used in 3 turns, etc. The computer doesn't have to do that chunking, each stone is evaluated individually. As such, the play-style was totally foreign to people. It did things no player had tried or, importantly, could have thought of given the limits of our brains having to 'chunk' the information. I would predict that a b-ball-bot would play the same way, in totally strange ways that a human can't think of. Exp: Calculating a reasonably high probability that the ball will bounce off your nose and go into the left hand of it's team-mate, throwing the ball as hard as it can at it's own head to make a shot, not trying to get past just 1 opponent but the entire team's right thighs 57 seconds from now, etc. Similarly with jazz, the computer is a dumb machine that will just do strange things because humans have to 'chunk'. In music, we play in chords and notes and with rhythm and timing. The computer can evaluate the whole song, and every other song at the same time and can borrow from all those. You and I can pull in the feelings of loss of a child, or the joy of strawberry ice-cream bars in a Memphis summer, things a computer will never. But we cannot pull in the obscure Tuvan throat singing techno-remixes on Youtube , the Afro-Thai heavy metal Vimeo channels, or the terrible pre-teen angst poems set to crappy guitar, etc, all at once. It can only see what you feed it, but you can feed it the life-outputted-into-music of billions of humans with live updates. The computer will know more. But music is emotional and about feelings. The feel of music is most important to us. And I think that a human songwriter is therefore essential, one that cares and puts effort into the work. It connects us, and that is what is important, not the sounds.

cdr 11y ago
> But music is emotional and about feelings. The feel of music is most important to us. And I think that a human songwriter is therefore essential, one that cares and puts effort into the work. It connects us, and that is what is important, not the sounds. Children can play music very emotionally (or rather, in a way that adults associate with emotional) without having any experience of or real comprehension of the emotions. Imitation and training is sufficient to be convincing. A program doesn't need to experience emotion, only know that certain characteristics of the sound are associated with certain emotions.

mjn 11y ago

There's a little work on that part of jazz too, though not much. My undergrad supervisor built a solo-trading jazz system about 15 years ago for her PhD thesis. Solo trading isn't the full extent of jazz improvisation, but is at least getting at one of the collaborative parts of jazz. It's now slightly dated, but I think still good work, and could probably sound a lot better if the same basic approach was taken but updated with today's hardware and algorithms. Thesis: http://reports-archive.adm.cs.cmu.edu/anon/anon/2001/abstracts/01-138.html http://reports-archive.adm.cs.cmu.edu/anon/anon/2001/abstrac... A conference paper: http://www.aaai.org/Papers/AAAI/2000/AAAI00-100.pdf http://www.aaai.org/Papers/AAAI/2000/AAAI00-100.pdf

rryan 11y ago

> Generating random patterns that sound jazz-ish is interesting, but until multiple generators can react to what the other is doing in real time (or to a human participant), it isn't exactly jazz. For an arbitrarily complex network, it could internally develop independent generators that react to each other. However, the likelihood of common optimization strategies used for training RNNs (back-propagation through time, foveation/attention, etc.) developing a network like this is probably quite small. It would be possible for a network designer to come up with a structure (as Hochreiter did with LSTMs) that lends itself to this sort of structure but then you're baking in assumptions about how humans accomplish a task (which comes with trade-offs).