Laminae: A stochastic modeling-based autonomous performance rendering system that elucidates performer characteristics

This paper proposes a system for performance rendering of keyboard instruments. The goal is fully autonomous rendition of a performance with musical smoothness without losing any of the characteristics of the actual performer. The system is based on a method that systematizes combinations of constraints and thereby elucidates the rendering process of the performer’s performance by defining stochastic models that associate artistic deviations observed in a performance with the contextual information notated in its musical score. The proposed system can be used to search for a sequence of optimum cases from the combination of all existing cases of the existing performance observed to render an unseen performance efficiently. Evaluations conducted indicate that musical features expected in existing performances are transcribed appropriately in the performances rendered by the system. The evaluations also demonstrate that the system is able to render performances with natural expressions stably, even for compositions with unconventional styles. Consequently, performances rendered via the proposed system have won first prize in the autonomous section of a performance rendering contest for computer systems.