
Synthesizers are musical instruments that typically expose a large set of user-adjustable parameters that shape the sound of the instrument. In this paper, we examine how leveraging low-dimensional latent representations of synthesizer patches enables musicians to generate new patches via exploration of a generative model's latent space. We evaluate two different latent representations, Latent Coordinates and Timbral Representation, through a mixed-methods user study (n=18). In our study, a mix of novice and experienced musicians engage with both sound matching and sound discovery tasks. Our qualitative results highlight a number of key themes regarding the suitability of our technique with each being supported through related quantitative results. Finally, these results indicate several ways in which this type of support tool may be used in a musician's existing creative workflow as well as provide a context for discussing the benefits of continuous interactions for generative systems as it relates to creative activities.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
