Music, Gesture, and Embodiment: New Interdisciplinary Perspectives in Gesture–Sound Studies

Dear Colleagues,

We kindly invite you to consider submitting a manuscript to our Special Issue, entitled ‘Music, Gesture, and Embodiment: New Interdisciplinary Perspectives in Gesture–Sound Studies’.

Over the past few decades, music research has increasingly embraced embodied perspectives, shifting focus from viewing music primarily as an abstract, intellectual endeavor to exploring its meaning through corporeal, multi-sensory experiences. This shift aligns with the increasing traction of embodied music cognition, which places the body at the core of our cognitive system in musical expression and experience, emphasizing the profound interconnection between movement and sound. The main premise underlying embodied music cognition is that music is inextricably linked with the sensation of movement, essentially being a part of it, in ways that are impossible to separate or disentangle. Our understanding of music is profoundly shaped by our prior experience of sensory– motor processes; in other words, we may perceive salient musical features as non-verbal multimodal phenomena that are closely tied to movement. Hence, there is a more fundamental movement– sound relationship that goes beyond merely mechanical couplings (predictable cause-effect relationship of gesture and sound governed by the principles of physics in sound-producing gestures) to include other types of links between sound and music-related gestures too.

Embodiment is especially prominent in oral music traditions, whereby knowledge is directly transmitted between teacher and disciple through demonstration, emulation, and repetition in face- to-face settings and includes not only sound but also essential corporeal information.

This Special Issue seeks to gather the latest advancements in the study of embodied music performance, perception and pedagogy, reinforcing the idea that music is as much a physical, multimodal, body-related phenomenon as it is an auditory one. It aims to bring together scholars   from a broad spectrum of disciplines—such as (ethno-)musicology, (ethno-)choreology, systematic musicology, psychology, philosophy, neuroscience, computer science, engineering, etc.—particularly those that challenge traditional approaches and offer innovative interdisciplinary methodologies, perspectives, and tools. Research that straddles the boundary between humanities and the sciences and that engages with the latest theoretical, empirical (both qualitative and quantitative) and technological approaches is strongly encouraged, as are works on oral music and dance traditions.

Topics of interest may include (but are not limited to):

• Interdisciplinary approaches to studying gestures and sound in music.
• The role of the body in music performance, composition and education.
• Theoretical frameworks, empirical methods and technological tools for understanding the relationship between music, gesture and embodiment across different musical traditions and genres.
• Cognitive and neuroscientific perspectives on the role of movement in musical experience and perception.
• The role of dance and movement in shaping musical structure and meaning.
• Embodied performance and instruction practices in various cultural contexts, with an emphasis on oral music and dance traditions.
• Cross-disciplinary approaches that integrate musicology, ethnomusicology, cognitive science, anthropology and philosophy.
• Latest trends in gesture–sound studies within musicology and ethnomusicology.
• Development of multimodal datasets for analyzing gesture–sound relationships.
• Innovative technologies in capturing and representing multimodal data in music (e.g., motion capture, virtual reality or wearable sensors).
• Advancements in motion capture technologies within music research (e.g., pose estimation and markerless optical/video-based systems).
• Motion capture approaches and technologies in ethnomusicological fieldwork.
• Machine learning techniques in studying gesture–sound relationships.
• Digital technologies in music performance and instruction (VR/AR/XR).
• Embodied aspects of technology-mediated music performance and instruction.
• Computational methods for the automated extraction of multimodal features from large datasets. 
• New interfaces for musical expression.

We look forward to your submissions.

Dr. Stella Paschalidou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Arts is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• embodied music cognition
• music and gesture
• gesture–sound relationship
• gesture analysis
• motion capture technologies
• multimodality
• interdisciplinary approaches
• video-based gesture recognition
• multimodal interaction
• video-based gesture recognition