Learning to listen, listening to learn

Pearce, M. T. (2025). Learning to listen, listening to learn: Music perception and the psychology of enculturation. Oxford University Press. https://doi.org/10.1093/oso/9780198848004.001.0001

What accounts for the variety of music witnessed across the world? The answer lies in the psychological mechanisms of cultural evolution that combine a creative process of composing ever new forms of music and a perceptual process of learning to appreciate listening to them.

This book develops and tests a theory of the psychological mechanisms that enable listeners to learn the structure of their culturally-situated musical environments so as to be able to perceive and appreciate music. The central hypothesis is that music perception depends critically on mechanisms of statistical learning and probabilistic prediction. These mechanisms are implemented in a computational model whose behaviour is analysed in detail through simulations of psychological experiments. The results demonstrate that the model can account for predictions generated by listeners for the pitch, timing and harmonies of music. While prediction is an important psychological mechanism in and of itself, the evidence presented shows how it also lays the foundation for a broader account of music perception, encompassing memory, auditory scene analysis, similarity perception, complexity perception, affect and aesthetic experience.

The proposed theory makes concrete predictions for differences in perception between listeners from different cultures and the developmental trajectories that result in these differences. These predictions are tested and corroborated with respect to both the incidental cultural experience of non-musicians and the formal cultural training of musicians. Because the approach rests fundamentally on mechanisms of statistical learning, it generalises naturally to other cultural domains including natural language, visual media and dance.

Testimonials

"A superb work of scholarship. A tour de force of technical rigour leading to lots of interesting musical insights and presented through an informative historical research narrative." - Professor David Huron, Ohio State University, USA

"A landmark contribution that bridges computational modelling, information theory, and music cognition in unprecedented ways. [...] Learning to Listen, Listening to Learn stands as a major achievement that successfully demonstrates how rigorous mathematical frameworks can formalize, predict, and explain cultural phenomena." - Dr Gilberto Bernardes, University of Porto, Portugal

"Learning to Listen, Listening to Learn illuminates one of the most fascinating questions in cognitive science: how the brain learns from experience. Through an elegant computational account grounded in music perception, it reveals principles that extend far beyond music to learning in the sensory environment more generally. Technically sophisticated and remarkably intuitive, it is likely to become a seminal reference for years to come." - Dr Roberta Bianco, University of Pisa, Italy

"Learning to Listen, Listening to Learn, is a deep and timely investigation of the role of enculturation in shaping music perception and pleasure. [...] The book deserves to become a classic, alongside key antecedents from Leonard Meyer, Carol Krumhansl, and David Huron, all of which are strongly referenced." - Professor Roger Dean, MARCS Institute for Brain, Behaviour and Development, Australia

Availability

Hardback available from Oxford University Press.
Hardback and e-book available from Amazon.
Online access available from Oxford Academic.

Sample material

Preview up to p. 32 (part way through Chapter 2) on Google books.
The table of contents.
The list of references.

Audio examples

Figure 2.2 (p. 32): Melody from a chorale harmonised by J. S. Bach (BWV 379).

Figure 3.1 (p. 76): Franz Schubert, Octet in F Major (D. 803), fourth movement.

(a) mm. 1-2.

(b) mm. 21-22.

Figure 4.1 (p. 94): J. S. Bach, Cello Suite No. 3 (BWV 1009), Bourrée, opening motif, mm. 0-2.

Figure 4.2 (p. 95): J. S. Bach, Cello Suite No. 4 (BWV 1010), Sarabande, opening motif, mm. 1-3.

Figure 4.3 (p. 97): The stimulus from Prince et al., (2009b) Experiments 1 and 2.

Figure 4.4 (p. 105): A chord sequence adapted from Koelsch et al. (2002), Figure 1, transposed into G major.

Figure 4.5 (p. 106): Cadence types from W. A. Mozart’s keyboard sonatas (Sears et al., 2019).

(a): Perfect authentic cadence (K. 281, i, mm. 5-8).

(b): Imperfect authentic cadence (K. 311, i, mm. 1-4).

(c): Half cadence (K. 333, iii, mm. 60–64).

(d): Deceptive cadence (K. 457, i, mm. 42–48).

(e): Evaded cadence (K. 281, ii, mm. 96–99).

Figure 5.2 (p. 134): Edgar Varèse, Density 21.5.

Figure 6.2 (p. 167): W. A. Mozart, Symphony No. 40 in G minor (K. 550), opening melody.

Figure 6.5 (p. 175): J. S Bach, Prelude 15 (BWV 884) from the Well-Tempered Clavier Book II (mm. 9-12).

Figure 7.1 (p. 200): German and Chinese folk melodies illustrating cultural distance.

(a) German melody (deut1445) with greatest cultural distance from the Chinese corpus.

(b) Chinese melody (han0418) with greatest cultural distance from the German corpus.