Robo Rocker: How Artificial Intelligence Wrote Beatles-Esque Pop Song
Robo Rocker: How Artificial Intelligence Wrote
Beatles-Esque Pop Song
By Jesse Emspak, Live Science Contributor | September 30,
2016 06:17am ET
When researchers recently unveiled the first pop song
composed by an artificial intelligence (AI) system, some creative types may
have been nervous about the idea of robots taking over their jobs. But how
exactly was AI used to write a song?
A team from the Sony CSL Research Lab used a system
called Flow Machines to compose the new record, titled "Daddy's Car."
The song sounds like a lost Beatles track from the late
1960s, or perhaps a composition by Brian Wilson of the Beach Boys. François
Pachet, the project's lead researcher, told Live Science that the song wasn't
created by an AI entirely from scratch, so composers can breathe easy — at
least for now. [Super-Intelligent Machines: 7 Robotic Futures]
The song's lyrics, surreal as they sound, were written by
a human, French composer Benoît Carré. The team also put together a second
track, called "Mr. Shadow," designed to incorporate the styles of Irving
Berlin, Duke Ellington, George Gershwin and Cole Porter.
The parts that were written by the computer are known as
the "lead sheet," which defines the song's melody, part of the
orchestration and part of the mix (which ordinarily audio engineers would then
complete). The user, in this case Carré, first chose a style of orchestration.
A piece of software called Flow Composer used a database of 13,000 lead sheets
to map the style to the lead sheet — that is, take the melody and make it fit
the style of music.
"The user has to select the orchestration style from
a palette of styles — actually styles here, are human recordings of existing
single songs. For instance, a Brazilian guitarist has recorded 'Girl from
Ipanema,' [and] we can select this recording, and it is mapped onto the lead
sheet," Pachet told Live Science in an email.
The software can then fit the style of the base song —
for example, an old Beatles track — to the melody. "If there are chords in
the lead sheets that were not played in the audio, the system can still use
chord substitutions and audio transformations so that it still 'fits,'"
Pachet said. What this means is the artificial intelligence can substitute in
music if the specific chords weren't in the song used as a base — the Beatles
in this example
Final choices are still left up to the user — for example
if the user doesn't like the accompaniments that the AI came up with — but
Pachet said in the future, these decisions could be automated as the
researchers build a bigger database of which accompaniments "work"
better with certain types of melodies. The machines could be taught this, via a
kind of reinforcement learning; greater weights would be assigned to the
"right" kinds of answers, and eventually an AI could learn what choices
sound better to human ears.
Still, there are things that the system does not do well,
Pachet said. "The hard part is now high-level 'structure,' or what I call
"sense of direction" — i.e., the capacity to establish long-term
correlations between elements of the piece (sequence). That is the thing we
(and others) are working on currently," he said.
Teaching an AI the "global timbre" of a song is
also difficult, Pachet said. A human can say "this song sounds like
X," but computers are not good at that kind of holistic thinking, he said.
Lyrics, as it happens, could be written by machine, he
added, but the technology isn't yet integrated into Flow Machine.
That said, the individual pieces that will give AI the
ability to compose might come together in the future, he added. "Basically,
all the basic ingredients are out there, and the trick is to put the pieces
together," Pachet said.
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