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Record W1988334109 · doi:10.1121/1.4780663

Beamforming for a microphone array embedded in asymmetrically shaped objects

2003· article· en· W1988334109 on OpenAlexaff
Philippe Moquin, Stéphane Dedieu, Rafik Goubran

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2003
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsCarleton UniversityMitel (Canada)
Fundersnot available
KeywordsBeamformingAcousticsMicrophone arrayMicrophoneBroadbandComputer scienceInvariant (physics)Rotational symmetryPhysicsMathematicsGeometryTelecommunications

Abstract

fetched live from OpenAlex

Broadband frequency invariant beamforming for circular arrays or linear arrays are quite common but not when they are embedded in a diffracting structure. Meyer [J. Acoust. Soc. Am. 109, 185–193 (2001)] describes arrays embedded in a diffracting sphere, and provides an analytical solution for the wave equation in acoustics. For arrays of simple shape like circular rings embedded in a more complex shape one must make use of numerical methods (e.g., boundary element methods). Microphone arrays in shapes that are not symmetric or axisymmetric can also be solved this way but result in very asymmetrical beams. One example of such an obstacle is a telephone incorporating a microphone array. This presentation will show results from simulations and measurements of a six-microphone array. A design approach to obtain reasonably well behaved beams relies on constrained optimization, with a constraint build using a set of vectors containing the sensor signal for acoustic waves with specific directions of arrival. [Work supported in part by Carleton University.]

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.289
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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
GenreMethods

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

Citations1
Published2003
Admission routes1
Has abstractyes

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