cellular automata music generation

16
CELLULAR AUTOMATA MUSIC GENERATION Rich French 3/2/13 Advisor: Kristina Striegnitz

Upload: adsila

Post on 23-Feb-2016

63 views

Category:

Documents


0 download

DESCRIPTION

Cellular Automata Music Generation. Rich French 3/2/13 Advisor: Kristina Striegnitz. Game of Life. A cell is “born” if it is surrounded by 2 neighbors A cell “survives” if it is surrounded by 2 or 3 neighbors Else, the cell dies or remains dead. How is a CA music?. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Cellular Automata Music Generation

CELLULAR AUTOMATA MUSIC GENERATION

Rich French3/2/13

Advisor: Kristina Striegnitz

Page 2: Cellular Automata Music Generation

Game of Life A cell is “born” if it is surrounded by 2

neighbors A cell “survives” if it is surrounded by 2

or 3 neighbors Else, the cell dies or remains dead

Page 3: Cellular Automata Music Generation

How is a CA music?

Simply extend the lines to another space and you have a grid!

If a quarter note is played, “alive” and if there is no note played “dead”

Page 4: Cellular Automata Music Generation

Goal The goal of our project is to create a

musical representation for CAs that emphasizes the different features inherent in a musical piece

If the songs generated are interesting, then this might shed light on the possibilities of computers to do high level tasks like music composition.

Page 5: Cellular Automata Music Generation

Cellular Automata Life We need rules that are sparse yet complex Some rules include, Seeds (B2), AntiLife

(B0123478/S01234678), HighLife (B36/S23)

Excitable medium K states, if state is g, g either stays the same or Turns into g+1 state

Page 6: Cellular Automata Music Generation

Musical Features Melody Scales Note placement Song structure Rhythm

Page 7: Cellular Automata Music Generation

Previous Work Eduardo Miranda’s CAMUS system Cartesian Representation: x and y

designate half steps from a base note Problem: Note order arbitrary, not much

variety for note placement Serquera and Chareyron alter sounds at

the wave-level Problem: Too open ended, not all sound

waves necessarily translate to music

Page 8: Cellular Automata Music Generation

The Representation

Layered CA system like CAMUS system The entire CA representation represents a

song Melody is represented by a Life

Automaton

Page 9: Cellular Automata Music Generation

The Representation

Each vertical column is a note or rest Notes grouped horizontally can be grouped

together to form longer notes The smallest length a note can be is 1/16 Horizontal length of the automaton is 16*#

of measures

Page 10: Cellular Automata Music Generation

The Representation Excitable medium CAs represent the

other components of the piece Note Placement (Blank spaces are

arbitrary)

16 states, For each note of 2 or more cells, a change of state from left to right designates a note separation.

Page 11: Cellular Automata Music Generation

The Representation Excitable medium CAs represent the

other components of the piece Scale (if yellow = C Major):

# of states = # of scales, the most represented scale for each column will be the current scale played

Page 12: Cellular Automata Music Generation

Example SongHigh Life (B36/S23)

Page 13: Cellular Automata Music Generation

Tools Golly: Open source CA program, allows

PERL scripting Allows for layering, very robust support of

different CA rules MIDI Perl: Perl module for creating MIDI

files Simple interface, with all the MIDI

features needed.

Page 14: Cellular Automata Music Generation

Evaluation

Page 15: Cellular Automata Music Generation

Results From Experiment We just finished the experiment, and are

working to make it work on all platforms. However, just listening to one or a few of

the songs, it’s clear that something is amiss

Page 16: Cellular Automata Music Generation

Conclusions/Future Work Murphy’s Law: When you create a system

open enough to create a wide variety of songs, you create opportunity for a wide variety of failure.

Uncanny Valley: When songs have musical elements, but it doesn’t come together with the same results of a human composer.

Possible changes to the software: Make the system more rigid, make it so there are less opportunities to sound strange. Add instrumentation.