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Record W3049713972 · doi:10.5281/zenodo.4813169

Vodhrán: collaborative design for evolving a physical model and interface into a proto-instrument

2020· article· en· W3049713972 on OpenAlexfundno aff
Laurel Pardue, Miguel Ortiz, Maarten van Walstijn, Paul Stapleton, Matthew Rodger

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2020
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsInterface (matter)Computer scienceHuman–computer interactionOperating system

Abstract

fetched live from OpenAlex

This paper reports on the process of development of a virtual-acoustic proto-instrument, Vodhrán, based on a physical model of a plate, within a musical performance-driven ecosystemic environment. Performers explore the plate model via tactile interaction through a Sensel Morph interface, chosen to allow damping and localised striking consistent with playing hand percussion. Through an iteration of prototypes, we have designed an embedded proto-instrument that allows a bodily interaction between the performer and the virtual-acoustic plate in a way that redirects from the perception of the Sensel as a touchpad and reframes it as a percussive surface. Due to the computational effort required to run such a rich physical model and the necessity to provide a natural interaction, the audio processing is implemented on a high powered single board computer. We describe the design challenges and report on the technological solutions we have found in the implementation of Vodhrán which we believe are valuable to the wider NIME community.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations1
Published2020
Admission routes1
Has abstractyes

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