Expression extraction in virtuoso music performances

An approach to music interpretation by computers is discussed. A rule-based music interpretation system is being developed that generates sophisticated performance from a printed music score. The authors describe the function of learning how to play music, which is the most important process in music interpretation. The target to be learned is expression rules and grouping strategy: expression rules are used to convert dynamic marks and motives into concrete performance data, and grouping strategy is used to extract motives from sequences of notes. They are learned from a given virtuoso performance. The delicate control of attack timing and of the duration and strength of the notes is extracted by the music transcription function. The performance rules are learned by investigating how the same or similar musical primitives are played in a performance. As for the grouping strategy, the system analyzes how the player grouped music and registers dominant note sequences to extract motives