The Data-Driven Algorithmic Composer

The Data-Driven Algorithmic Composer (D-DAC) is an application designed to output data-driven algorithmically composed music via MIDI. The application requires input data to be in tab-separated format to be compatible. Each dataset results in a unique piece of music that remains consistent with each iteration of the application. The only varying elements between each iteration of the same dataset are factors defined by the user: tempo, scale, and intervals between rows. Each measure of the melody, harmony and bassline is derived from each row of the dataset. By utilizing this non-random algorithmic application, users can create a unique and predefined musical iteration of their dataset. The overall aim of the D-DAC is to inspire musical creativity from scientific data and encourage the sharing of datasets between various research communities.

[1]  Popularisation within the Sciences , 1985 .

[2]  C. Palisca,et al.  A History of Western Music , 1960 .

[3]  Roberto Bresin,et al.  A Systematic Review of Mapping Strategies for the Sonification of Physical Quantities , 2013, PloS one.

[4]  Helge Ritter,et al.  SONIFICATIONS FOR EEG DATA ANALYSIS , 2002 .

[5]  A. Supper Lobbying for the ear : the public fascination with and academic legitimacy of the sonification of scientific data , 2012 .

[6]  D. McNeill,et al.  MICA : A Hybrid Method for Corpus-Based Algorithmic Composition of Music Based on Genetic Algorithms , Zipf ’ s Law , and Markov Models , 2013 .

[7]  Gerhard Nierhaus,et al.  Algorithmic Composition: Paradigms of Automated Music Generation , 2008 .

[8]  Bruce Jacob,et al.  Composing with Genetic Algorithms , 1995, ICMC.

[9]  Damon Horowitz,et al.  Generating Rhythms with Genetic Algorithms , 1994, AAAI.

[10]  Nicolas Privault,et al.  Understanding Markov Chains: Examples and Applications , 2013 .

[11]  Andy Hunt,et al.  Interactive sonification of complex data , 2009, Int. J. Hum. Comput. Stud..

[12]  Kevin I. Jones,et al.  Compositional Applications of Stochastic Processes , 1981 .

[13]  Vincent Larivière,et al.  Scientists Popularizing Science: Characteristics and Impact of TED Talk Presenters , 2013, PloS one.

[14]  Nicolas Privault,et al.  Understanding Markov Chains , 2013 .

[15]  A. Supper Sublime frequencies:  The construction of sublime listening experiences in the sonification of scientific data , 2014, Social studies of science.

[16]  Elliott Schwartz,et al.  Music Since 1945: Issues, Materials, and Literature , 1993 .