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Record W2139888099 · doi:10.1109/icassp.2001.940348

An acoustic echo cancellation structure for synthetic surround sound

2002· article· en· W2139888099 on OpenAlexafffund
Trevor Yensen, Rafik Goubran

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLoudspeakerEcho (communications protocol)Computer scienceSurround soundAudio feedbackVirtual realityTeleconferencePath (computing)AcousticsSpeech recognitionSound (geography)Human–computer interactionMultimediaComputer network

Abstract

fetched live from OpenAlex

This paper proposes an acoustic echo cancellation structure for hands-free synthetic surround sound applications, such as multiple participant conferencing, and virtual reality applications. Voice over Internet protocol (VoIP) and other virtual reality applications can benefit from the addition of 3D spatial audio generated by more than two loudspeakers. When full-duplex audio is present in a system, however, acoustic echo cancellation is required to eliminate the feedback echo path. The acoustic echo cancellation structure proposed by this paper is based on the acoustic echo canceller per spatial region allocation scheme previously introduced by the authors for two channel synthetic stereo. This paper shows that the spatial region allocation scheme is extensible to any number of channels which makes it extremely versatile and flexible, especially for surround sound audio. Microsoft Direct X 7, a commonly used application programmer interface (API), was used in our simulations to generate the 3D spatial audio on a PC.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.308

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 communication0.0000.001
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 head0.022
GPT teacher head0.256
Teacher spread0.234 · 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 designSimulation or modeling
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

Citations2
Published2002
Admission routes2
Has abstractyes

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