Modeling Human Experts’ Identification of Orchestral Blends Using Symbolic Information

Orchestral blend happens when sounds coming from two or more instruments are perceived as a single sonic stream. Several studies have suggested that different musical properties contribute to create such an effect. We developed models to identify orchestral blend effects from symbolic information taken from scores based on calculations related to three musical parameters, namely onset synchrony, pitch harmonicity, and parallelism in pitch and dynamics. In order to evaluate the performance of the models, we applied them to different orchestral pieces and compared the outputs with human experts’ ratings available in the Orchestration Analysis and Research Database (Orchard). Using different thresholds for the three parameters under consideration, the models were able to successfully retrieve 81% of the instruments involved in an orchestral blend on average. These results suggest that symbolic representation of music conveys perceptual information. However, further developments including audio analyses to take into account timbral properties could alleviate some of the current limitations.