Neural Network Drum Track Composition

Dan Smith

Goal

• Develop a neural net which can be trained to produce drum tracks given a few starting beats.

Previous work

• Michael Mozer – Neural Network Music composition by prediction

• Adam Guetz and Tony Lee – Neural Network Music Composition

Network

• Each note is presented to network, the network predicts next note.

• Training mode– At each note, error is calculated based on next

note– Weights are updated

• Simulation mode– Next note is fed back into network

Network architecture

Next note

Context

Note selector

Neural Network

Note representation

• Note is respresented at duration and instruments

• Six instruments: snare, tom1, tom2, cymbal, hi-hat, bass.

Instrument Representation

• Instruments are represented in binary, 1 means the instrument is being played, 0 means it is not

• Vector is (snare, tom1, tom2, cymbal, hi-hat, bass)

Duration representation

• Time is divided into ticks. Each tick represents 1/12 of a beat. – Eighth note = 6 ticks– Eighth note triplet = 4 ticks

• Note is represented by elapsed time, as well as (elapsed time mod 4) and (elapsed time mod 3)

Why?

• Eighth notes = sixteenth notes mod 3– 3 mod 3 = 0– 6 mod 3 = 0

• Eight note triplets = quarter note triplets mod 4– 4 mod 4 = 0– 8 mod 4 = 0

Duration(cont)

• Each mod is represented by a 1 hot code– Eg 6 mod 4 = 2 = 0100– 6 mod 3 = 0 = 001

Total representation

• 14 until vector

• (duration, mod4 (4 inputs), mod3 (3 inputs), snare, tom1, tom2, cymbal, hi-bat, bass)

Converting Output to Next Note

• Duration is distributed, must pick real duration

• Pick duration vector closest to the duration produced by the network

Results

• Network learned simple patterns without repeated note (analogous to previous work)

• Network learned patterns with repeated notes

• Did not generalize well

Future suggestions

• Work on generalization– Problem with context resetting

• Try top down production Method

References

• Michael Mozer – Neural network music composition by prediction– http://www.cs.colorado.edu/~mozer/papers/

music.html

• Tony Lee and Adam Guetz – Neural Network Music compostion – http://www3.hmc.edu/~anlee/cs152/