Modeling the contribution of auditory scene analysis principles to perceptual effects of orchestration

Abstract

Auditory Scene Analysis (ASA) research has provided knowledge about the principles underlying auditory organization processes and has been successfully applied in computational ASA. Based on these findings, we applied these principles within a musical context. The aim is to understand and computationally model the perception of effects, such as blend and segregation, created by the combining and contrasting of properties of traditional Western instruments which result from three auditory processes: concurrent, sequential, and segmental grouping. The initial aim was to evaluate the extent to which the symbolic data provided in a musical score provide sufficient data to model the perception of these orchestral effects. Preliminary implementations have achieved an average accuracy score of 81%, suggesting that perceptual effects of orchestration can be partially retrieved by calculations based on ASA principles using symbolic data. However, many cases indicate that including properties of the acoustic signal would enhance the predictive power. This approach also provides us with the means to investigate the relative weights of the different principles involved in these grouping processes in order to understand their relative importance in musical contexts. These findings contribute to the creation of a framework for studying and understanding the perceptual characteristics of orchestration practice.