TY - GEN A1 - Bavister, P PB - European Acoustics Association (EAA) KW - Evolutionary Computation KW - Biometric Sensing KW - Neural Networks KW - Virtual Acoustics N1 - © 2023 First author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. SP - 6411 N2 - This paper describes a series of experiments to engage intelligent systems and biometric sensing in a reciprocally creative relationship between computer composed music and physical space, accessing correlations between spatial volume, materiality, and performance. The paper will review tests undertaken at UCL in 2022, in evolving site-specific music using virtual acoustics, evolutionary programming, and biometric sensing. The paper will describe and define the toolsets involved, neural networks to determine note generation and periodicity, evolutionary processes to determine sequencing and emotional response as a fitness function and summarises how these were applied. The analysis of the outputs is compared against the room?s acoustic data for correlations and relationships. Metrics to seek correlations against tempo fluctuations are T30, T20, EDT and C80. The output of the tests gives us clues as to what future music is likely to appeal emotionally in such spaces for differing listeners? demographics. As the spaces chosen were not typical acoustic musical venues, there are no preconceived ideas about what would or should not sound acceptable in each. If music can evolve to suit a space, then surely each space, however acoustically detrimental, can host something that can be viewed as aesthetically pleasing and site specific. UR - http://doi.org/10.61782/fa.2023.0306 EP - 6418 ID - discovery10190486 SN - 2221-3767 Y1 - 2023/09/15/ TI - Biometrically Evolved Site-Specific Music as a Response to Localised Acoustic Conditions AV - public ER -