Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation

Engineering and Physical Sciences Research Council (EPSRC) funding via grant EP/M000702/1

Perceptual representations mediate effects of stimulus properties on liking for music.

Perceptual pleasure and its concomitant hedonic value play an essential role in everyday life, motivating behavior and thus influencing how individuals choose to spend their time and resources. However, how pleasure arises from perception of sensory information remains relatively poorly understood. In particular, research has neglected the question of how perceptual representations mediate the relationships between stimulus properties and liking (e.g., stimulus symmetry can only affect liking if it is perceived). The present research addresses this gap for the first time, analyzing perceptual and liking ratings of 96 nonmusicians (power of 0.99) and finding that perceptual representations mediate effects of feature-based and information-based stimulus properties on liking for a novel set of melodies varying in balance, contour, symmetry, or complexity. Moreover, variability due to individual differences and stimuli accounts for most of the variance in liking. These results have broad implications for psychological research on sensory valuation, advocating a more explicit account of random variability and the mediating role of perceptual representations of stimulus properties

Multiple Viewpoint Systems: Time Complexity and the Construction of Domains for Complex Musical Viewpoints

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Effects of pitch and timing expectancy on musical emotion

Pitch and timing information work hand in hand to create a coherent piece of music; but what happens when this information goes against the norm? Relationships between musical expectancy and emotional responses were investigated in a study conducted with 40 participants: 20 musicians and 20 non-musicians. Participants took part in one of two behavioural paradigms measuring continuous expectancy or emotional responses (arousal and valence) while listening to folk melodies that exhibited either high or low pitch predictability and high or low onset predictability. The causal influence of pitch predictability was investigated in an additional condition where pitch was artificially manipulated and a comparison conducted between original and manipulated forms; the dynamic correlative influence of pitch and timing information and its perception on emotional change during listening was evaluated using cross-sectional time series analysis. The results indicate that pitch and onset predictability are consistent predictors of perceived expectancy and emotional response, with onset carrying more weight than pitch. In addition, musicians and non-musicians do not differ in their responses, possibly due to shared cultural background and knowledge. The results demonstrate in a controlled lab-based setting a precise, quantitative relationship between the predictability of musical structure, expectation and emotional response.Comment: 53 pages, 5 figures; Submitted to Psychomusicolog

PPM-Decay: A computational model of auditory prediction with memory decay

Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies—one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment—we show how this decay kernel improves the model’s predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm)

Musical Features for Automatic Music Transcription Evaluation

This technical report gives a detailed, formal description of the features introduced in the paper: Adrien Ycart, Lele Liu, Emmanouil Benetos and Marcus T. Pearce. "Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription", Transactions of the International Society for Music Information Retrieval (TISMIR), Accepted, 2020

Simulating melodic and harmonic expectations for tonal cadences using probabilistic models

<p>This study examines how the mind’s predictive mechanisms contribute to the perception of cadential closure during music listening. Using the Information Dynamics of Music model (or IDyOM) to simulate the formation of schematic expectations—a finite-context (or <i>n</i>-gram) model that predicts the next event in a musical stimulus by acquiring knowledge through unsupervised statistical learning of sequential structure—we predict the terminal melodic and harmonic events from 245 exemplars of the five most common cadence categories from the classical style. Our findings demonstrate that (1) terminal events from cadential contexts are more predictable than those from non-cadential contexts; (2) models of cadential strength advanced in contemporary cadence typologies reflect the formation of schematic expectations; and (3) a significant decrease in predictability follows the terminal note and chord events of the cadential formula.</p

Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns

This study was funded by a Deafness Research UK fellowship and Wellcome Trust Project Grant 093292/Z/10/Z (to M.C.)

Simultaneous Consonance in Music Perception and Composition

Simultaneous consonance is a salient perceptual phenomenon corresponding to the perceived pleasantness of simultaneously sounding musical tones. Various competing theories of consonance have been proposed over the centuries, but recently a consensus has developed that simultaneous consonance is primarily driven by harmonicity perception. Here we question this view, substantiating our argument by critically reviewing historic consonance research from a broad variety of disciplines, reanalyzing consonance perception data from 4 previous behavioral studies representing more than 500 participants, and modeling three Western musical corpora representing more than 100,000 compositions. We conclude that simultaneous consonance is a composite phenomenon that derives in large part from three phenomena: interference, periodicity/harmonicity, and cultural familiarity. We formalize this conclusion with a computational model that predicts a musical chord’s simultaneous consonance from these three features, and release this model in an open-source R package, incon, alongside 15 other computational models also evaluated in this paper. We hope that this package will facilitate further psychological and musicological research into simultaneous consonance