Live Coding with an Affective Autonomous Agent in TidalCycles- Performance

https://aimc2023.pubpub.org/pub/vnkwhmgn

This submission proposes a musical performance that combines the improvisational skills of a live coder with an autonomous music creation system, developed and implemented using Haskell and the TidalCycles language. The system uses machine learning algorithms to generate its own unique musical phrases and patterns that respond to the live coding input. The performance will showcase the collaborative possibilities of this technology, demonstrating how it can facilitate a real-time dialogue between human and machine intelligence. The proposed performance will consist of an evolving musical improvisation, that explores the interaction between the live coder and the autonomous system. A discussion of the technical aspects of the system, including the algorithms used, the data sources and input methods is also included. Overall, this performance presents a unique and innovative approach to musical performance that demonstrates new creative capabilities for live coders through machine collaboration.