How Music Moves

Eitan, Zohar; Granot, Roni

doi:10.1525/mp.2006.23.3.221

Cited by 185 publications

(74 citation statements)

References 82 publications

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“…The results extend previous reports for the musical domain (Lipscomb & Kim, 2004;, and complements work on more general associations of auditory and spatial mappings in movement (Eitan & Granot, 2006;Burger, Thompson, Luck, Saarikallio & Toiviainen, 2013). However, as Eitan & Timmers (2010) note, it is possible that other visual and metaphorical features interact with how one represents crossmodal mapping and this should be further refined.…”

Section: Discussionsupporting

confidence: 88%

What do we know about implicit false-belief tracking?

2014

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Visualizing acoustic features of speech has proven helpful in speech therapy; however, it is as yet unclear how to create intuitive and fitting visualizations. To better understand the mappings from speech sound aspects to visual space, a large web-based experiment (n=249) was performed to evaluate spatial parameters that may optimally represent pitch and loudness of speech. To this end, five novel animated visualizations were developed and presented in pairwise comparisons, together with a static visualization. Pitch and loudness of speech were each mapped onto either the vertical (y-axis) or the size (z-axis) dimension, or combined (with size indicating loudness and vertical position indicating pitch height) and visualized as an animation along the horizontal dimension (x-axis) over time. The results indicated that firstly, there is a general preference towards the use of the y-axis for both pitch and loudness, with pitch ranking higher than loudness in terms of fit. Secondly, the data suggest that representing both pitch and loudness combined in a single visualization is preferred over visualization in only one dimension. Finally, the z-axis, although not preferred, was evaluated as corresponding better to loudness than to pitch. This relation between sound and visual space has not been reported previously for speech sounds, and elaborates earlier findings on musical material. In addition to elucidating more general mappings between auditory and visual modalities, the findings provide us with a method of visualizing speech that may be helpful in clinical applications such as computerized speech therapy, or other feedback-based learning paradigms.

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Section: Discussionsupporting

confidence: 88%

What do we know about implicit false-belief tracking?

2014

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“…Similar with previous findings [11,16,17,33], our study indicates that subjects have an intuitive tendency to associate musical structures with physical space and bodily motion. The analysis of the extracted movement features shows that the corporeal resonance behaviour in response to the oneto-many alternation in the auditory stimuli is characterised by a contraction/expansion of the upper limbs in the subjects' peripersonal space.…”

Section: Discussionsupporting

confidence: 92%

“…This study will focus on the relation between the dynamically changing pattern of the upper limbs in terms of contraction and expansion and the communication of musical expressiveness. The choice for this particular movement feature is made in line with findings of previous research indicating that: (I) music intuitively stimulates movement in the peripersonal space [11,16,17,33], (II) the human body is an important channel of affective communication [3,10,14,15,36], (III) the upper body features are most significant in conveying emotion and expressiveness [23], (IV) the movement size and openness can be related to the emotional intensity of the musical sound production [6,13], and (V) an open body position in contrast to a closed body position reinforces the communicator's intent to persuade [29,30]. It is assumed that a better understanding of the connection between this spatio-kinetic movement feature and expressive features in relation to multimodal interfaces may provide a cue to the solution of the mapping problem in a number of application contexts.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

From expressive gesture to sound

Maes

Leman

Lesaffre

et al. 2009

J Multimodal User Interfaces

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This paper contributes to the development of a multimodal, musical tool that extends the natural action range of the human body to communicate expressiveness into the virtual music domain. The core of this musical tool consists of a low cost, highly functional computational model developed upon the Max/MSP platform that (1) captures real-time movement of the human body into a 3D coordinate system on the basis of the orientation output of any type of inertial sensor system that is OSC-compatible, (2) extract low-level movement features that specify the amount of contraction/expansion as a measure of how a subject uses the surrounding space, (3) recognizes these movement features as being expressive gestures, and (4) creates a mapping trajectory between these expressive gestures and the sound synthesis process of adding harmonic related voices on an in origin monophonic voice. The concern for a user-oriented and intuitive mapping strategy was thereby of central importance. This was achieved by conducting an empirical experiment based on theoretical concepts from the embodied music cognition paradigm. Based on empirical evidence, this paper proposes a mapping trajectory that fa-P.-J. Maes ( ) · M. Leman · M. Lesaffre · M. Demey · cilitates the interaction between a musician and his instrument, the artistic collaboration between (multimedia) artists and the communication of expressiveness in a social, musical context.

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“…Since understanding musical change as movement is an important way in which music has been thought to convey information, auditory metaphors in descriptions of music are used extensively to convey vast amounts of information about dynamic processes, such as movement (Gjerdingen, 1994;Johnson & Larson, 2003;Todd, 1992). Moreover, listeners can certainly understand some of these musical devices as intended: Eitan and Granot (2006) asked participants to imagine movement as they heard several short music motifs, and they found consistent mappings between the manipulation of certain musical parameters (e.g., pitch, acceleration) and bodily movement.…”

mentioning

confidence: 99%

Music can elicit a visual motion aftereffect

Hedger

Nusbaum

Lescop

et al. 2013

Atten Percept Psychophys

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Motion aftereffects (MAEs) are thought to result from the adaptation of both subcortical and cortical systems involved in the processing of visual motion. Recently, it has been reported that the implied motion of static images in combination with linguistic descriptions of motion is sufficient to elicit an MAE, although neither factor alone is thought to directly activate visual motion areas in the brain. Given that the monotonic change of musical pitch is widely recognized in music as a metaphor for vertical motion, we investigated whether prolonged exposure to ascending or descending musical scales can also produce a visual motion aftereffect. After listening to ascending or descending musical scales, participants made decisions about the direction of visual motion in random-dot kinematogram stimuli. Metaphoric motion in the musical stimuli did affect the visual direction judgments, in that repeated exposure to rising or falling musical scales shifted participants' sensitivity to visual motion in the opposite direction. The finding that music can induce an MAE suggests that the subjective interpretation of monotonic pitch change as motion may have a perceptual foundation.

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How Music Moves

Cited by 185 publications

References 82 publications

What do we know about implicit false-belief tracking?

What do we know about implicit false-belief tracking?

From expressive gesture to sound

Music can elicit a visual motion aftereffect

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