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Record W2059323339 · doi:10.1121/1.4778768

Validating a new approach for predicting the degree of speech security

2005· article· en· W2059323339 on OpenAlexaff
Bradford N. Gover, John S. Bradley

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsIntelligibility (philosophy)Degree (music)Computer scienceSpeech recognitionAcousticsNoise (video)Artificial intelligencePhysics

Abstract

fetched live from OpenAlex

The new method of estimating the speech security of meeting rooms first predicts transmitted speech levels at spot positions 0.25 m from the outside boundaries of a meeting room. The degree of speech security at each spot measurement position is related to this transmitted speech level and to the ambient noise level at the same location. This information can be used to calculate new signal/noise ratio measures that indicate the degree of speech security [J. Acoust. Soc. Am. 116(6), 3480–3490 (2004)]. The values of these indices will indicate whether speech will be audible or intelligible, and to what degree. This paper reports validation studies of the prediction of transmitted speech levels at points 0.25 m outside the meeting room, and the effects of varied room absorption on these predicted levels. It also reports on subjective evaluations of the transmitted speech sounds, in terms of the audibility and intelligibility of the transmitted speech, to validate expected judgments in realistic acoustical conditions.

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)0.007
metaresearch head score (Gemma)0.028
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.277
Teacher spread0.235 · 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
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
Published2005
Admission routes1
Has abstractyes

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