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Abstract
The controlled manipulation of digitally generated sound in computer music affords new opportunities to investigate the cognitive accessibility of musical features additional to pitch and rhythm. Experiments investigated listeners' detection of segments in computer-generated material, ranging from obvious (Experiment 1) to more subtle and undetectable segmentation (Experiment 2). Experiment 3 compared segment detection using headphones to using loudspeakers. Results indicate that listeners not selected for musical expertise can detect segmentation efficiently, but complex individual algorithmically generated segments were interpreted as comprising multiple segments. In addition, an increase in sonic texture was better detected than a decrease of the same magnitude.
Acknowledgements
The research reported in this paper is supported by an Australian Research Council“Discovery” grant (DP0453179) held by Roger Dean. We would like to thank Michael Kubovy, Kate Stevens, and two anonymous reviewers for their helpful comments on earlier versions of this manuscript.
Notes
Sonograms were made with C. Lauer's Sonogram software, developed at the German Research Center for Artificial Intelligence and available on the web (http://sourceforge.net/projects/sonogram). The circular object below 2.2 kHz in the sonogram, appearing just after the onset of FB04, is a graphic artefact of the Sonogram programme.
Please note that listeners could not be wrong in their judgement: the term “error” is simply used for the purposes of data analysis to denote a different response than the prescribed algorithmic composition.