Over the past few years, the concepts of Artificial Intelligence (AI) and Machine Learning (ML) have not only established themselves as experimental research fields but have also become versatile toolsets with creative applications. While there have been notable breakthroughs and widespread adoption in text-based generation (as seen with ChatGPT) and image-based generation (as exemplified by DALL-E), musical generation tools have yet to witness broad adoption in terms of public use and artistic endeavors. By utilizing data in the form of audio recordings and musical mappings, AI algorithms can learn, process, and replicate patterns and stylistic elements found in complex musical systems, all without the need for explicitly defined generation methods.
The proposed project seeks to investigate and develop specific artistic methodologies for utilizing musical AI tools in the collaborative human-machine creative process. This endeavor will involve the study and application of data generated by the artist-researchers within the CREATIE research group. Several artist-researchers within CREATIE are currently engaged in incorporating machine learning into their creative works, with the aim of refining and developing new approaches, methodologies, and skills. Furthermore, their artistic research activities have produced a substantial volume of material well-suited for the Machine Learning process.
(c) Wannes Cré
