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Record W2077921803 · doi:10.1121/1.3384667

Comparative study of a proposed time varying loudness standard for common sounds.

2010· article· en· W2077921803 on OpenAlexaff
Colin Novak, Helen Ule, Tomasz Łętowski

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2010
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLoudnessComputer scienceAcoustics

Abstract

fetched live from OpenAlex

Several calculation procedures exist and are standardized for the determination of loudness of steady sounds. While loudness models for unsteady sounds do presently exist, they differ in their outcomes and have not been yet sufficiently validated using round robin or other appropriate evaluation methodology. Recently, the Deutsches Institut fur Normung (DIN) announced that it will soon issue a new standard describing a method for calculation of loudness of time-varying sounds. However, the DIN 45631-A1 takes a less common approach in that it does not fully describe a methodology to calculate the unsteady loudness. It instead offers a more general procedure along with open-ended checks and balances for verifying the progress through the various calculation steps. The caveat of this is that while conditions specified by this standard may be satisfied, varying results may be achieved due to the procedures’ open architecture. Conversely, the checks and balances may be enough such that identical results are achieved for the same sounds. This study investigates several commercial applications using this standard and compares their results for several common inputs. The results of the study will be discussed in terms of the extent to which compliance with DIN 45631-A1 results in identical loudness scores.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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