Room Acoustics and Musical Performance: New Predictors for Acoustical Conditions on Stage

• Applicant: Professor Dr. Stefan Weinzierl
• Subject Area: Acoustics
• Term: since 2013
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 244251882

The project "Raumakustik und musikalische Interpretation", of which a final report is presented, has investigated if and in what way the acoustic conditions during a musical performance influence the way of playing and singing of instrumental and vocal performers with respect to tempo, dynamics and timbral rendition. It has not only shown which general interrelationships exist, and to what extent these depend on the musical instrument and on the personality of the individual musician. The project has also delivered a Stage Acoustical Quality Inventory (STAQI), i.e., a consensus vocabulary of room acoustical qualities from the perspective of musicians consisting of 17 items and 5 factors. The continuation proposal presented aims at identifying room acoustical parameters which can serve as technical predictors for these qualities. While the limited validity of the two parameters currently suggested in ISO 3382-1 for stage conditions is widely acknowledged, a variety of new parameters were suggested during the last two decades, none of which, however, has found its way into room acoustic planning so far. The present project aims to take a decisive step in this direction by creating a large stimulus pool for the assessment of stage acoustic conditions for different musical ensemble types (solo / chamber music / symphony orchestra) with different musicians and different musical repertoire on the basis of systematically varied acoustic conditions. These systematic variations will be realized with advanced room acoustic simulation and dynamic binaural synthesis, with particular attention to diffraction effects by musicians and music stands on stage, while the STAQI will be used as a measuring instrument for a differentiated assessment of the acoustic conditions. The analysis will use General Additive Models and Multivariate Adaptive Regression Splines aiming at selecting optimal predictors for each STAQI factor and estimating also non-linear effects and interactions of the selected predictors. The best parameters identified will be cross-validated by analyzing the perceptual assessments of musicians immediately after their performance as well as the effect on their performance itself, both underlining the relevance of the stage acoustical features represented by these parameters.

• DFG Programme: Research Grants