Investigating Instrument Identification in a Virtual Orchestral Scene

Musical scene analysis (MSA) in an orchestral context is affected by the spatial positioning of instruments on stage, the reverberation of the concert hall, and the musical structure itself. Although studies have investigated the perceptual blending of instruments in musical mixtures, instrument identification has mostly been studied for sounds in isolation. How the acoustic and musical variables affect identification performance remains unclear. In the present study we used a cue-mixture identification paradigm to have participants identify eight sustained instruments in twelve short four-instrument mixtures taken from Wagner’s Tristan prelude. Excerpts were rendered with and without concert hall acoustics using a room-acoustic modeling software with instruments either spread out on stage or all in a single center location. Against initial hypotheses, reverberation of the virtual concert hall and spatial distribution of instruments did not affect identification performance, despite clear effects on sound quality ratings. On the other hand, instrument-dependent musical effects of voice, register, and acoustical content were observed. These results hint at instrument identification performance showing robustness to variations in acoustic conditions and highlight the complex nature of instrument perception in realistic sound mixtures.