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Record W2016830532 · doi:10.1121/1.428975

Eyes ’n ears: A system of attentive teleconferencing

2000· article· en· W2016830532 on OpenAlexaff
Bill Kapralos, Michael Jenkin, John K. Tsotsos, Evangelos Milios

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2000
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsDalhousie UniversityYork University
Fundersnot available
KeywordsTeleconferenceComputer scienceMicrophoneSound (geography)Intersection (aeronautics)Microphone arrayAcoustic spaceAcousticsSource trackingAcoustic source localizationSpeech recognitionTelecommunicationsSound pressureEngineeringPhysics

Abstract

fetched live from OpenAlex

Various teleconferencing systems exist, including systems intended for multiple speakers where a speaker must be localized. Although many sound-localization systems are available, not only are they expensive and nonportable, most require extensive audio arrays resulting in substantial computational processing. A simple, economical, and compact method of sound localization for use in a teleconferencing system is being investigated. In order to localize a sound source, this system relies solely on ITD measurements between microphone pairs, which allows the sound source to be determined as one of many possible locations on the surface of a cone. By taking the intersection of a sufficient number of cones, the location of a sound source in three-dimensional space may be determined. Our goal is to overcome the problems associated with the sound-localization systems currently available. In particular, this work seeks to develop an affordable, limited maintenance and compact sound-localization system for use with a teleconferencing system capable of locating and tracking a speaker in a multiple speaker setting.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.749
Threshold uncertainty score0.241

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 science0.0010.000
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 head0.228
Teacher spread0.219 · 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 designOther design
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

Citations2
Published2000
Admission routes1
Has abstractyes

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