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Record W4396774676 · doi:10.1007/978-3-031-57892-2_9

Embodied Sonic Design: Sound and the Sensory Apprehension of Movement

2024· book-chapter· en· W4396774676 on OpenAlexaff
Gemma L. Crowe

Bibliographic record

VenueCurrent research in systematic musicology · 2024
Typebook-chapter
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsEmily Carr University of Art and Design
Fundersnot available
KeywordsEmbodied cognitionMovement (music)Sound (geography)ApprehensionSensory systemAcousticsCommunicationPsychologyComputer scienceCognitive psychologyPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Sound acts as an extension of the body, created by movement and received as vibration. I am focused on the removal of a visual representation of the body as a template; to instead facilitate an embodied experience. As an embodied practitioner, I create immersive sound and media installations derived from recordings of my own moving body. The movement of sound depicts the presence of a body in motion through sensory illusion. Through embodied sonic design, my sound recordings decontextualize, abstract, and reframe the auditory experience. I physically manipulate the recording of sound to perceptually rematerialize the moving physical form during playback with two techniques: sound shadows and embodied binaural spatialization . These techniques encourage the listener to perceive sound and space with the same awareness that situates their body, such as sensation and proprioception. The perceived physical interaction within the reception of this sound is akin to a kinesthetic projection and is an engagement in spatial thinking, activating mirror neurons and kinesthetic empathy. Creating awareness through physical attunement can regulate systems out of balance by offering the embodiment of alternative states: shifting how one thinks and feels in a particular setting. My research seeks to recognize the listener’s unique perspective through their individual body.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.213
GPT teacher head0.372
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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