Abstract

Composers often pick specific instruments to convey a given emotional tone in their music, partly due to their expressive possibilities, but also due to their timbres in specific registers and at given dynamic markings. Of interest to both music psychology and music informatics from a computational point of view is the relation between the acoustic properties that give rise to the timbre at a given pitch and the perceived emotional quality of the tone. Musician and nonmusician listeners were presented with 137 tones produced at a fixed dynamic marking (forte) playing tones at pitch class D# across each instrument's entire pitch range and with different playing techniques for standard orchestral instruments drawn from the brass, woodwind, string, and pitched percussion families. They rated each tone on six analogical-categorical scales in terms of emotional valence (positive/negative and pleasant/unpleasant), energy arousal (awake/tired), tension arousal (excited/calm), preference (like/dislike), and familiarity. Linear mixed models revealed interactive effects of musical training, instrument family, and pitch register, with non-linear relations between pitch register and several dependent variables. Twenty-three audio descriptors from the Timbre Toolbox were computed for each sound and analyzed in two ways: linear partial least squares regression (PLSR) and nonlinear artificial neural net modeling. These two analyses converged in terms of the importance of various spectral, temporal, and spectrotemporal audio descriptors in explaining the emotion ratings, but some differences also emerged. Different combinations of audio descriptors make major contributions to the three emotion dimensions, suggesting that they are carried by distinct acoustic properties. Valence is more positive with lower spectral slopes, a greater emergence of strong partials, and an amplitude envelope with a sharper attack and earlier decay. Higher tension arousal is carried by brighter sounds, more spectral variation and more gentle attacks. Greater energy arousal is associated with brighter sounds, with higher spectral centroids and slower decrease of the spectral slope, as well as with greater spectral emergence. The divergences between linear and nonlinear approaches are discussed.

Highlights

  • The relationship between music and emotion has become a widely studied topic

  • The aim was to determine the acoustic properties related to timbre that contribute to ratings by musician and nonmusician listeners on continuous scales of the emotional qualities valence, tension arousal and energy arousal

  • To analyze the contribution to the emotion ratings of acoustic properties related to timbre, we examined 23 acoustic signal parameters taken from the Timbre Toolbox (Peeters et al, 2011), spanning spectral, temporal, and spectrotemporal audio descriptors

Read more

Summary

Introduction

The relationship between music and emotion has become a widely studied topic. Its existence is undeniable and multiple studies have revealed that for most people the predominant motivation for listening to and engaging in music is its emotional impact (Sloboda and O’Neill, 2001; Krumhansl, 2002; Juslin and Laukka, 2004). We examine musical instrument timbre and the audio descriptors derived from the sound signal that contribute to its timbre in relation to a three-dimensional model of perceived affect. We develop linear regression and nonlinear neural net models to establish a computational link between audio descriptors and perceived emotion ratings, providing a basis for a music informatics approach to the role of timbre in emotion perception

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call