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Record W2109233160 · doi:10.5072/zenodo.205731

Different strokes: a prototype software system for laptop performance and improvisation

2006· article· en· W2109233160 on OpenAlexaff
Mark Zadel, Gary Scavone

Bibliographic record

VenueNew Interfaces for Musical Expression · 2006
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsLaptopComputer scienceInterface (matter)ImprovisationSoftwareHuman–computer interactionGraphical user interfaceUser interfaceMultimediaOperating system

Abstract

fetched live from OpenAlex

This paper presents progress in the design of a new software interface for laptop performance and improvisation. These performances can lack a sense of active creation, as well as a visual connection between the performer's actions and the audio output. This stems partly from certain patterns in laptop performance in which musicians resort to heavy automation to cope with performing complex compositions. The software presented here attempts to address this by requiring that the user create all of the control sequences on-stage. The user defines graphical control patterns that are mapped to sample playback. The current prototype resembles a freehand drawing interface where the strokes create looping and cascading animations that generate corresponding audio, ultimately creating music. This style of interface minimizes the use of prepared material and takes advantage of the computer's unique capabilities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.008

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 head0.014
GPT teacher head0.234
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations16
Published2006
Admission routes1
Has abstractyes

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