The impact of 3-D sound spatialisation on listeners’ understanding of human agency in acousmatic music

We are interested in learning how listeners perceive sounds as having human origins. An experiment was performed with a series of electronically synthesized sounds, and listeners were asked to compare them in pairs. We propose a Bayesian probabilistic method to learn individual preferences from non-transitive pairwise comparison data, as happens when one (or more) individual preferences in the data contradicts what is implied by the others. We build a Bayesian Mallows model in order to handle non-transitive data, with a latent layer of uncertainty which captures the generation of preference misreporting. We then develop a mixture extension of the Mallows model, able to learn individual preferences in a heterogeneous population. The results of our analysis of the musicology experiment are of interest to electroacoustic composers and sound designers, and to the audio industry in general, whose aim is to understand how computer generated sounds can be produced in order to sound more human.

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“…A complete description of the background, hypotheses, experimental setup, and discussion of results in Barrett and Crispino (2018).…”

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confidence: 99%

A Bayesian Mallows approach to nontransitive pair comparison data: How human are sounds?

Crispino¹,

Arjas²,

Vitelli³

et al. 2019

Ann. Appl. Stat.

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Toward a human-like sound perception for reactive virtual agents

Couzon,

Pichard,

Zimmermann

et al. 2023

Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents

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Perceptual Recognition of Sound Trajectories in Space

Schumacher

Espinoza

Mardones

et al. 2021

Computer Music Journal

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Sound spatialization is a technique used in various musical genres as well as in soundtrack production for films and video games. In this context, specialized software has been developed for the design of sound trajectories we have classified as (1) basic movements, or image schemas of spatial movement; and (2) archetypal geometric figures. Our contribution is to reach an understanding of how we perceive the movement of sound in space as a result of the interaction between an agent's or listener's sensory-motor characteristics and the morphological characteristics of the stimuli and the acoustic space where such interaction occurs. An experiment was designed involving listening to auditory stimuli and associating them with the aforementioned spatial movement categories. The results suggest that in most cases, the ability to recognize moving sound is hindered when there are no visual stimuli present. Moreover, they indicate that archetypal geometric figures are rarely perceived as such and that the perception of sound movements in space can be organized into three spatial dimensions—height, depth, and width—which the literature on sound localization also confirms.

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The impact of 3-D sound spatialisation on listeners’ understanding of human agency in acousmatic music

Cited by 3 publications

References 23 publications

A Bayesian Mallows approach to nontransitive pair comparison data: How human are sounds?

A Bayesian Mallows approach to nontransitive pair comparison data: How human are sounds?

Toward a human-like sound perception for reactive virtual agents

Perceptual Recognition of Sound Trajectories in Space

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