The Audience Reception of Algorithmic Music

Algorithmic music composition has been part of the lexicon since the mid-twentieth century. Due to the manifestation of Moore’s Law, we have witnessed an exponential growth in computing power. Contemporary music research and practice have leveraged these advances by integrating computing devices into many aspects of music– from generative music to live-coding. This efflorescence of musical practice, process, and product raises complex issues in audience reception (Miranda 2001). Since there is every indication that the exploration and exploitation of technology will continue unabated, it is essential that we understand the psychological aspects of audience reception of algorithmic music (Collins 2009).

This chapter employs a comparative analysis in a longitudinal study designed to advance our understanding of the psychological aspects of the audience reception of algorithmic music. The four compositions studied are Barry Truax’s Riverrun, Elliot Carter’s Canon for Three Equal Instruments, Mara Helmuth’s Abandoned Lake in Maine, and Krzysztof Penderecki’s Threnody for the Victims of Hiroshima. These pieces were selected because they were composed during the latter part of the twentieth-century and were presented on fixed media to avoid variability in musical performance. The primary mode of data collection is through the language of the audience using a modified think-aloud protocol. The premise of this study is that reception theory may be applied to the audience reception of algorithmic music using a cognitive-affective model to further understand the process of decoding of meaning. This study puts forth a robust methodology for future longitudinal and comparative research in the audience reception of music and makes recommendations for further research.