LLMs for performers¶
Performers occupy a distinct position in the music AI landscape. Unlike listeners, who engage with music episodically, or producers, who work in creative sessions with the goal to produce or edit tracks, performers maintain a long-term relationship with their instrument, their repertoire, and the physical act of playing. This chapter follows that relationship through three layers: Machine perception of performance data (preliminaries for performance MIR), turning evidence into feedback and assessment (bridging performance and language), and sustaining coaching across time with agentic systems.