What Pinnipeds Have to Say about Human Speech, Music, and the Evolution of Rhythm

Ravignani, Andrea; Fitch, W. Tecumseh; Hanke, Frederike D.; Heinrich, Tamara; Hurgitsch, Bettina; Kotz, Sonja A.; Scharff, Constance; Stoeger, Angela S.; Boer, Bart de

doi:10.3389/fnins.2016.00274

Cited by 56 publications

(60 citation statements)

References 120 publications

(138 reference statements)

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“…The birds-by far the longest list when counting individual species (in the thousands [9])comprise songbirds (Passeriformes), parrots (Psittaciformes), and hummingbirds (Trochiliformes) [10,11]. The mammals include humans, some cetaceans [12,13], pinnipeds [14,15], elephants [16], and bats [17,18]. Birds are considered closest to humans in vocal learning abilities, even though they are phylogenetically the most remote.…”

Section: The "Canonical" List Of Vocal Learnersmentioning

confidence: 99%

Vocal learning: Beyond the continuum

Martins¹,

Boeckx²

2020

PLoS Biol

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Vocal learning is the ability to modify vocal output on the basis of experience. Traditionally, species have been classified as either displaying or lacking this ability. A recent proposal, the vocal learning continuum, recognizes the need to have a more nuanced view of this phenotype and abandon the yes-no dichotomy. However, it also limits vocal learning to production of novel calls through imitation, moreover subserved by a forebrain-to-phonatorymuscles circuit. We discuss its limitations regarding the characterization of vocal learning across species and argue for a more permissive view.

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Section: The "Canonical" List Of Vocal Learnersmentioning

confidence: 99%

Vocal learning: Beyond the continuum

Martins¹,

Boeckx²

2020

PLoS Biol

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“…For these reasons, I argue that phase space plots can offer systematic benefits at extremely low cost in experimental research on music production, entrainment, and human movement as an initial diagnostic tool. Beyond the benefits described above, this could systematize the analysis of rhythm production across experiments, which would be particularly useful in studies examining groups of two or more participants (Clayton, 2007), cross-species comparisons (which should be free from top-down assumptions; Ravignani, Fitch, et al, 2016;Wilson & Cook, 2016), and crosscultural convergence of rhythmic features (Trehub, 2015) either in different musical cultures (Le Bomin, Lecointre, & Heyer, 2016) or in musical experiments in the lab (Ravignani, Delgado, & Kirby, 2016), all of which are core components of modern attempts to understand the biology and evolution of music (Fitch, 2006;Ravignani & Cook, 2016).…”

Section: Discussionmentioning

confidence: 99%

Visualizing and Interpreting Rhythmic Patterns Using Phase Space Plots

Ravignani

2017

Music Perception

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Structure in musical rhythm can be measured using a number of analytical techniques. While some techniques—like circular statistics or grammar induction—rely on strong top-down assumptions, assumption-free techniques can only provide limited insights on higher-order rhythmic structure. I suggest that research in music perception and performance can benefit from systematically adopting phase space plots, a visualization technique originally developed in mathematical physics that overcomes the aforementioned limitations. By jointly plotting adjacent interonset intervals (IOI), the motivic rhythmic structure of musical phrases, if present, is visualized geometrically without making any a priori assumptions concerning isochrony, beat induction, or metrical hierarchies. I provide visual examples and describe how particular features of rhythmic patterns correspond to geometrical shapes in phase space plots. I argue that research on music perception and systematic musicology stands to benefit from this descriptive tool, particularly in comparative analyses of rhythm production. Phase space plots can be employed as an initial assumption-free diagnostic to find higher order structures (i.e., beyond distributional regularities) before proceeding to more specific, theory-driven analyses.

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“…One of the most important overarching set of research questions relates to the special (or possibly unique) position of human language in relation to the signaling systems used by other living systems, and how we acquired it as a species (Fitch, 2000;Knight et al, 2000;MacNeilage, 2008;Tomasello, 2008;Berwick et al, 2013;Ravignani et al, 2016;Vernes, 2016). Likewise, it is often asked whether the patterning of birdsong is similar to speech or, perhaps, more related to music (Shannon, 2016).…”

Section: Comparative Analysis Of Human and Animal Vocalizationmentioning

confidence: 99%

Vocal Interactivity in-and-between Humans, Animals, and Robots

2016

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Almost all animals exploit vocal signals for a range of ecologically motivated purposes: detecting predators/prey and marking territory, expressing emotions, establishing social relations, and sharing information. Whether it is a bird raising an alarm, a whale calling to potential partners, a dog responding to human commands, a parent reading a story with a child, or a business-person accessing stock prices using Siri, vocalization provides a valuable communication channel through which behavior may be coordinated and controlled, and information may be distributed and acquired. Indeed, the ubiquity of vocal interaction has led to research across an extremely diverse array of fields, from assessing animal welfare, to understanding the precursors of human language, to developing voice-based human-machine interaction. Opportunities for cross-fertilization between these fields abound; for example, using artificial cognitive agents to investigate contemporary theories of language grounding, using machine learning to analyze different habitats or adding vocal expressivity to the next generation of language-enabled autonomous social agents. However, much of the research is conducted within well-defined disciplinary boundaries, and many fundamental issues remain. This paper attempts to redress the balance by presenting a comparative review of vocal interaction within-and-between humans, animals, and artificial agents (such as robots), and it identifies a rich set of open research questions that may benefit from an interdisciplinary analysis.

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What Pinnipeds Have to Say about Human Speech, Music, and the Evolution of Rhythm

Cited by 56 publications

References 120 publications

Vocal learning: Beyond the continuum

Vocal learning: Beyond the continuum

Visualizing and Interpreting Rhythmic Patterns Using Phase Space Plots

Vocal Interactivity in-and-between Humans, Animals, and Robots

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