GANterpretations
This provides a tool for musicians and creators to explore multi-modal expression, but it is incremental as it builds on existing GAN techniques for creative applications.
The authors tackled the problem of automatically generating videos to accompany audio recordings by aligning GANs to spectral properties, enabling musicians to create AI-generated musical videos guided by performance and visual narratives.
Since the introduction of Generative Adversarial Networks (GANs) [Goodfellow et al., 2014] there has been a regular stream of both technical advances (e.g., Arjovsky et al. [2017]) and creative uses of these generative models (e.g., [Karras et al., 2019, Zhu et al., 2017, Jin et al., 2017]). In this work we propose an approach for using the power of GANs to automatically generate videos to accompany audio recordings by aligning to spectral properties of the recording. This allows musicians to explore new forms of multi-modal creative expression, where musical performance can induce an AI-generated musical video that is guided by said performance, as well as a medium for creating a visual narrative to follow a storyline (similar to what was proposed by Frosst and Kereliuk [2019]).