https://phys.org/news/2018-07-music-software-brand-fit.html

The algorithm extracts musical expressions as perceived by different target groups from audio signals and provides customised brand-fitting music for each context. To create such a system, researchers from ABC_DJ first developed a vocabulary with which to systematically describe music in the branding context. This novel "General Music Branding Inventory" was established with nine audio branding experts and refined by 305 marketing experts. The next step in the development process was to test this semantic inventory in the field. A 28,543-song pool was used from which 549 songs were selected for detailed evaluation. A large-scale listening experiment was then conducted in which 10,144 participants in Germany, Spain and the UK were asked to match semantic features to songs (e.g. modern, passionate, innovative, happy, trustworthy).

Statistical analysis of the results – over 53,344 measurements based on 2,018,704 data points – pinpointed the 36 features most relevant to both music and brands. The sample was balanced with regard to age, country and education to ensure representative insights into how different target groups perceive semantic expression in music. To operationalise these findings, it was necessary to map semantic features onto acoustic features.