Machine learning lets computer create melodies to fit any lyrics
Machine learning lets computer create melodies to fit any
lyrics
DAILY NEWS 9
December 2016
Got words but no melody? A machine learning system turns
poetry into song by composing a pop music score to suit the lyrics it’s given.
“I was studying singing while I was doing my PhD in
computer science,” says Margareta Ackerman at San Jose State University in
California, who developed the system with David Loker at technology advisory
firm Orbitwerks. “Over time, I started to think of computers as creative
partners instead of tools, which could maybe help me write songs.”
The system, called ALYSIA, processes short lines of text
and associates each syllable with a musical note. It chooses the pairing based
on features including the syllable’s position in the word and how it will fit
with the previous five notes.
ALYSIA can write whole accompanying scores this way, or
provide musicians with a variety of melody options for each segment of lyrics,
acting like a co-creator. Ackerman and Loker developed the system to produce
pop tunes, but say it could be adapted different genres. The system uses two
models, one focused on rhythm and the other on pitch. These were trained on the
melody line and lyrics of 24 different pop songs.
They then used the system to make melodies to accompany
two sets of words written by Ackerman that involved it coming up with tunes for
lyrics such as “Now that you’re gone / I just realised that I’m all alone”.
They also fed it the lyrics to the vaudeville classic I’m Always Chasing
Rainbows to see how it could reimagine the song in the pop genre.
Getting in tune
The idea of trying to automate musical composition is not
new, but David Cope at the University of California, Santa Cruz, says ALYSIA is
unusual in taking lyrics as its starting point. He is impressed that the system
manages to match the metre of the melody with that of the lyrics, but says the
compositions show an “almost annoying” lack of harmony.
Rebecca Fiebrink, a researcher in machine learning and
music at Goldsmiths, University of London, questions how useful the
lyrics-to-melody approach is. “Is this really solving the compositional process
for people who want to make music?” she says. “Creating a melody without
additional accompaniment, like this system does, is the easiest thing to
achieve.”
The songs admittedly aren’t about to win any Grammys, but
Ackerman says this is just the start. She initially imagined targeting ALYSIA
at the electronic music community, but is now working on repurposing it for professional
songwriters with the help of classical composers.
Ultimately, Ackerman hopes to create a system capable of
composing all aspects of a song on its own. “We want to design a program able
to generate the music, the lyrics, and ideally even the production and the
singing by itself,” she says.
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