Exploring emotional responses to orchestral gestures

Author:

Goodchild Meghan1,Wild Jonathan1,McAdams Stephen1

Affiliation:

1. McGill University, Canada

Abstract

Research on emotional responses to music indicates that prominent changes in instrumentation and timbre elicit strong responses in listeners. However, there are few theories related to orchestration that would assist in interpreting these empirical findings. This article investigates listeners’ emotional responses to four types of orchestral gestures – large-scale timbral and textural changes that occur in a coordinated, goal-directed manner – through an exploratory experiment that collected continuous responses of emotional intensity for musician and nonmusician listeners. A time series regression analysis was used to predict changes in emotional responses by modeling changes in several musical features, including instrumental texture, spectral centroid, loudness, and tempo. We demonstrate the application of a new visualization tool that compiles the emotional intensity ratings with score-based and performance-based musical features for qualitative and quantitative analysis. The results suggest that the response profiles differ for the four gestural types. Following the increasing growth of instrumental texture and loudness, the emotional intensity ratings climbed steadily for the gradual addition types. The ratings for the sudden addition gestures sharply increased in response to the rapid textural change, peaking toward the end of the excerpt. There was a slight tendency for musicians, but not nonmusicians, to anticipate the moment of sudden addition with heightened emotional responses. The responses to the reductive excerpts, both gradual and sudden, feature a plateau of lingering high emotional intensity, despite the decrease of other musical features. The visualization provided a method to observe the evolution of listeners’ emotional reactions in response to the orchestral gestures and assisted in interpreting the results of the time series regression analysis.

Funder

Social Sciences and Humanities Research Council of Canada

Fonds de Recherche du Québec-Société et Culture

Institute for the Public Life of Arts and Ideas

Centre for Interdisciplinary Research in Music Media and Technology

Canada Research Chairs

Publisher

SAGE Publications

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