MétaCan
Menu
Back to cohort
Record W2118571492 · doi:10.5072/zenodo.206209

Real-time Phase Vocoder Manipulation by Runner's Pace

2009· article· en· W2118571492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsMcGill University
Fundersnot available
KeywordsPaceComputer scienceSynchronization (alternating current)SIGNAL (programming language)NikeReal-time computingKinematicsSpeech recognitionSimulationTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a method for using a runner’s pace for real-time control of the time-scaling facility of a phase vocoder, resulting in the automated synchronization of an audio track tempo to the generated control signal. The in-crease in usage of portable music players during exercise has given rise to the development of new personal exercise aids, most notably the Nike+iPod system, which relies on embedded sensor technologies to provide kinematic work-out statistics. There are also systems that select songs based on the measured step frequency of a runner. The proposed system also uses the pace of a runner, but this information is used to change the tempo of the music.

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.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score0.277

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 communication0.0000.001
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 head0.016
GPT teacher head0.275
Teacher spread0.259 · 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

Quick stats

Citations22
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicMusic and Audio ProcessingFrench-language works237,207