Systems
A 23-stage DAG decomposes source video into multi-modal records, centroids, and provenance with consent-aware release posture.
Figure 1.ClipCannon materializes video into multi-modal records through a 23-stage analysis DAG.
The figure shows source video moving through a staged ClipCannon DAG. Analysis stages extract visual, semantic, emotion, speaker, prosody, sentiment, and voice-identity records. The outputs are persisted as multi-modal training and provenance records rather than one unstructured video blob.
Figure 2.The identity-locked video case remains protocol-level; subject-specific artifacts are withheld.
The figure represents a protocol-level video case. A single-subject interview is analyzed into curated clips and multi-modal labels. The research site treats the identity-locked talking-head result as protocol-level, with subject-specific artifacts withheld and end-to-end measurement pending.
ClipCannon transforms source video into structured multi-modal records through a 23-stage DAG. The relevant research point is source-grounded decomposition, not generic video editing.
The video-side panel provides visual, semantic, emotion, speaker, prosody, sentiment, and voice-identity views that can become a TCT-style target constellation.
Figure 3.ClipCannon supplies the modality centroids used by TCT-style runtime guard checks.
The diagram shows modality centroids from ClipCannon as a target constellation. Candidate outputs are projected through the same frozen instruments and accepted only when their modality projections remain within configured thresholds. The check is a panel-relative geometric predicate.
Voice and identity demonstrations are dual-use. This site names the method and scoped metrics but does not publish subject-specific clone artifacts.
measured
The published case reports 0.961 mean WavLM SECS on 10 held-out English sentences for one speaker under an encoder-matched protocol.
protocol-level
The manuscript treats the identity-locked talking-head case as architecturally complete but measurement-pending.
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Video-side DDA and TCT demonstration around multi-modal decomposition and identity centroids.
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Operational walkthrough for ClipCannon as a local video understanding and editing system.