MétaCan
Menu
Back to cohort
Record W4253759999 · doi:10.1121/1.4800452

Integration of a distance sensitive wireless communication protocol to hearing protectors equipped with in-ear microphones.

2013· article· en· W4253759999 on OpenAlexafffund
Rachel E. Bou Serhal, Tiago H. Falk, Jérémie Voix

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsInstitut National de la Recherche ScientifiqueÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersMitacs
KeywordsMicrophoneLoudspeakerComputer scienceWirelessEar canalSIGNAL (programming language)Noise (video)Channel (broadcasting)AcousticsTelecommunicationsEngineeringElectrical engineeringComputer visionPhysics

Abstract

fetched live from OpenAlex

Using radio communication in noisy environments is a practical and affordable solution allowing communication between workers wearing Hearing Protection Devices (HPD). However, typical radio communication systems have two main limitations when used in noisy environments: first, the background noise is disturbing the voice signal picked-up and transmitted, and second, that voice signal goes to all listeners on the same radio channel regardless of their physical proximity. A new concept of a so-called " Radio Acoustical Virtual Environment" (RAVE) addressing these two issues is presented. Using an intra-aural instantly custom molded HPD equipped with both an in-ear microphone and miniature loudspeaker, undisturbed speech is captured from inside the ear canal and transmitted over the wireless radio to the remote listener. The transmitted signal will only be received by listeners within a given spatial range, such range depending on the user's vocal effort and background noise level. This paper demonstrates the technological challenges to overcome and the methodology involved in the implementation of RAVE.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.581

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 communication0.0000.000
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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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 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

Citations6
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of meetings on acousticsSame topicTeleoperation and Haptic SystemsFrench-language works237,207