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Record W1489349645 · doi:10.1109/iscas.1995.521548

Lip synchronization in 3-D model based coding for video-conferencing

2002· article· en· W1489349645 on OpenAlexaff
Joseph A. Provine, L.T. Bruton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordssyncComputer scienceCoding (social sciences)Synchronization (alternating current)TeleconferenceSpeech recognitionScheme (mathematics)Sequence (biology)Data synchronizationComputer visionArtificial intelligenceMultimediaComputer networkMathematicsFrame (networking)

Abstract

fetched live from OpenAlex

One of the visually important aspects in a video-conferencing sequence is lip synchronization (lip-sync), particularly when a 3-D model based coding scheme is used to transmit the sequence. This issue has not been addressed so far by model based coding schemes. We present a technique to synchronize the lip movements to the audio associated with the sequence for a coding scheme that uses a muscle based facial model.

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 score0.704
Threshold uncertainty score0.263

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 head0.039
GPT teacher head0.246
Teacher spread0.207 · 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

Citations15
Published2002
Admission routes1
Has abstractyes

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