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Record W2043126530 · doi:10.1121/1.2839283

Evaluation of acoustical conditions for speech communication in working elementary school classrooms

2008· article· en· W2043126530 on OpenAlexaffabout
Hiroshi Satō, John S. Bradley

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsReverberationAcousticsRoom acousticsNoise (video)Architectural acousticsSpeech communicationAbsorption (acoustics)Computer sciencePhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Detailed acoustical measurements were made in 41 working elementary school classrooms near Ottawa, Canada to obtain more representative and more accurate indications of the acoustical quality of conditions for speech communication during actual teaching activities. This paper describes the room acoustics characteristics and noise environment of 27 traditional rectangular classrooms from the 41 measured rooms. The purpose of the work was to better understand how to improve speech communication between teachers and students. The study found, that on average, the students experienced: teacher speech levels of 60.4 dB A, noise levels of 49.1 dB A, and a mean speech-to-noise ratio of 11 dB A during teaching activities. The mean reverberation time in the occupied classrooms was 0.41 s, which was 10% less than in the unoccupied rooms. The reverberation time measurements were used to determine the average absorption added by each student. Detailed analyses of early and late-arriving speech sounds showed these sound levels could be predicted quite accurately and suggest improved approaches to room acoustics design.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.347
Teacher spread0.273 · 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 designObservational
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

Citations224
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicHearing Loss and RehabilitationFrench-language works237,207