Abstract
This paper introduces an approach for using a swarm intelligence algorithm, Stochastic Diffusion Search (SDS) – inspired by one species of ants, Leptothorax acervorum – in order to generate music from plain text. In this approach, SDS is adapted in such a way to vocalise the agents, to hear their “chit-chat”. While the generated music depends on the input text, the algorithm’s search capability in locating the words in the input text is reflected in the duration and dynamic of the resulting musical notes. In other words, the generated music depends on the behaviour of the algorithm and the communication between its agents. This novel approach, while staying loyal to the original input text, when run each time, ‘vocalises’ the input text in varying ‘flavours’.
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- 1.
Follow this link to listen to three runs of the music generated by the algorithm based on the input text ‘hello music sds welcome to the reality’: https://www.dropbox.com/s/bh4icqsdlpz04re/SDSMusic.zip?dl=0.
- 2.
While different, the similarities between all three music sheets are evident. In every run, the differences in note values and rest values are noticeable (i.e. by comparing all the first bars of all the three runs with each other, you can see how the note values are different and also there is one rest value in the third run).
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Al-Rifaie, A.M., Al-Rifaie, M.M. (2015). Generative Music with Stochastic Diffusion Search. In: Johnson, C., Carballal, A., Correia, J. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2015. Lecture Notes in Computer Science(), vol 9027. Springer, Cham. https://doi.org/10.1007/978-3-319-16498-4_1
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DOI: https://doi.org/10.1007/978-3-319-16498-4_1
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