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Record W2127390035 · doi:10.1109/89.902283

Synthetic stereo acoustic echo cancellation structure for multiple participant VoIP conferences

2001· article· en· W2127390035 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Speech and Audio Processing · 2001
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsCarleton University
Fundersnot available
KeywordsMonauralSpatializationEcho (communications protocol)Computer scienceStereophonic soundTeleconferenceLoudspeakerVoice over IPReverberationSpeech recognitionChannel (broadcasting)Artificial intelligenceAcousticsTelecommunicationsThe Internet

Abstract

fetched live from OpenAlex

This paper proposes a novel acoustic echo cancellation structure intended for multiple participant, full-duplex, hands-free voice over Internet protocol (VoIP) conferencing. A synthetic stereo image is generated through the use of spatialization functions, which are used to assist the near-end user in distinguishing between far-end talkers. The proposed synthetic stereo structure, which uses a single echo canceler per spatial region, is compared to structures with a single echo canceler per channel and to stereophonic echo cancelers. The proposed structure does not suffer from correlation of the reference signals, which can cause system misconvergence in structures that use a single canceler per channel. Correlation of the reference signals is eliminated since monaural signals are transmitted at the far-end and static spatialization functions are used at the near-end to allocate each participant to a spatial region.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.001
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 head0.040
GPT teacher head0.275
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