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Record W4383682964 · doi:10.1145/3563657.3596099

Multimodal Direct Manipulation in Video Conferencing: Challenges and Opportunities

2023· article· en· W4383682964 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

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceGestureModality (human–computer interaction)MultimediaHuman–computer interactionUsabilityVideoconferencingPopularityEmbodied cognitionComponent (thermodynamics)TeleconferenceAugmented realityInteractive mediaArtificial intelligence

Abstract

fetched live from OpenAlex

Tools supporting immersive live video conferencing (VC) have gained popularity recently across diverse application domains. A core component of the experience is augmenting video communication with multimodal interactive media. While many direct-manipulation techniques for VC communication have been proposed in existing literature, the usability and preferences for these techniques have never been formally studied. In this paper, we examine how embodied interaction democratizes content authoring, and propose a rehearsal-to-performance (RtP) framework along with a VC system, Clio, that enables performers to directly interact with their media using voice, gesture, and external devices such as tablets. We evaluate existing operation-to-modality mappings for VC communication, as well as describe novel mappings not present in the literature. A series of studies demonstrate modality preferences and potentials for incorporating real-time direct-manipulation tools to create expressive augmented VC performances.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.652
Threshold uncertainty score0.984

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 head0.278
GPT teacher head0.367
Teacher spread0.089 · 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

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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