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\newcommand{\vect}[1]{\boldsymbol{#1}}
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\setlength{\emergencystretch}{2em}
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\title{WHEN SHOULD AN EGOCENTRIC CONVERSATIONAL AGENT SPEAK? PROBING AND
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ADAPTING OMNI MODELS FOR MULTIPARTY FLOOR ACTION}
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\title{GLOBAL OMNI CONTEXT AND CAUSAL LOCAL AUDIOVISUAL EVIDENCE FOR
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EGOCENTRIC MULTIPARTY FLOOR-ACTION FORECASTING}
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% TODO: Insert the final author list and affiliations after the ICASSP 2027
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% review policy and author order are finalized.
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@@ -24,26 +24,28 @@ ADAPTING OMNI MODELS FOR MULTIPARTY FLOOR ACTION}
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\begin{abstract}
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An egocentric conversational agent operating among several people must decide
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whether to speak or keep listening before it generates a response. EgoSpeak
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operationalizes this problem using recordings from human camera wearers:
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causal first-person audio--video forms the observation, and the wearer's future
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speaking behavior forms the action target. The wearer is thus a data-collection
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surrogate rather than the deployed system. EgoSpeak evaluates
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separately extracted audio--visual features with Transformer, GRU, and Mamba
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temporal models; whether end-to-end pretrained omni models that jointly process
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raw audio and video expose the
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fine-grained cues required for a decision every 200~ms remains unclear. We
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probe representative omni backbones using frozen readout,
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parameter-efficient tuning, and causal side branches that preserve recent
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audio and visible-person evidence. The study tests whether a global omni state
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underrepresents other-person activity and whether local evidence compensates
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without making the agent passive. An EasyCom event protocol measures false
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agent entries during multi-other exchanges at matched recall of wearer-derived
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onset targets. Exploratory Qwen2.5-Omni-3B results motivate this hypothesis but
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do not yet establish a cross-model limitation or determine the final adapter.
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\todo{After the train-side study is locked, name the selected backbones and
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adapter and insert: frozen/PEFT/local deltas, multi-other false-entry reduction
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at 80\% onset recall, onset/yield non-degradation, and 95\% intervals.}
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whether to speak or keep listening before generating a response. Following
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EgoSpeak, we use causal first-person audio--video as observation and the future
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speaking behavior of the human camera wearer as an imitation target for this
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agent decision. We ask whether a jointly pretrained Omni model exposes the
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fine-grained floor cues required every 200~ms. Our global--local formulation
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uses a causal global Omni readout for broad scene and conversational context,
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while a causal local branch preserves recent mixed audio and a variable set of
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track-organized person observations. Anonymous tracks are an organizational
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interface whose incremental value must be established, not an assumption that
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the model knows speaker identity. On EasyCom development data, a single-seed
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oracle analysis finds that perfectly aligned aggregate activity among visible
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non-wearers improves 0.2-s mAP by 6.97 points and ten-horizon mean mAP by 2.91
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points over global Omni plus recent audio. Person-resolved histories do not
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outperform an identity-shuffled control. This result motivates timely local
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floor evidence, while explicitly withholding a person-continuity claim. The
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full study compares frozen, parameter-efficient, and learned local variants
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and evaluates false agent entry at matched wearer-onset recall.
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\todo{After the train-side study is locked, replace the final two sentences
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with the selected learned local variant and insert: its oracle-gap recovery,
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multi-other false-entry reduction at 80\% onset recall, onset/yield
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non-degradation, and 95\% intervals. Mention track continuity only if its
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controls separate.}
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\end{abstract}
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\begin{keywords}
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@@ -79,26 +81,39 @@ wav2vec2 feature extractors with Transformer/LSTR, single-layer GRU, and Mamba
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temporal models, forecasting the camera wearer and aggregate other-person
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activity over the next two seconds \cite{kim2025egospeak}. Thus our novelty is
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not the task definition or the use of first-person data. The unresolved model
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question is whether an end-to-end pretrained audio--visual omni backbone,
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question is whether a jointly pretrained audio--visual Omni backbone,
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operating on causal raw media, exposes an adequate state for this dense
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floor-action controller. To our knowledge, such omni representations have not been
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systematically evaluated or adapted for the EgoSpeak task.
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Our working hypothesis is specific. An omni model may retain broad scene and
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speech semantics while its global causal state makes recent prosody, activity
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boundaries, and individual visible-speaker motion difficult for a shallow
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5-Hz head to recover. This would appear as inaccurate prediction of
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other-person activity and poorly timed agent entries, especially in
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multiparty exchanges. A causal local side branch may compensate by preserving
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recent audio and anonymous person-level evidence before fusion with the global
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state. This is a hypothesis to test, not an assumed omni-model deficiency:
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frozen, parameter-efficiently tuned, and locally augmented variants must be
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compared within each backbone.
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Our working hypothesis is a representational decomposition. A global causal
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Omni state may retain broad scene, speech, and semantic context while making
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recent prosody, activity boundaries, and localized person motion difficult for
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a shallow 5-Hz controller to recover. A causal local branch therefore
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preserves recent mixed audio and a variable-size set of person observations
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before fusing them back into the global state. The local set can be pooled
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within a frame or organized into anonymous tracks across time. Whether that
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continuity adds useful information beyond aggregate activity is itself a
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falsifiable question. Frozen, parameter-efficiently tuned, and locally
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augmented variants must consequently be compared within each backbone.
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An initial causal oracle screen sharpens this hypothesis. On held-out EasyCom
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Session~12, perfectly timed aggregate activity from currently visible
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non-wearers improves a matched global-plus-audio model by 6.97 points at 0.2~s
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and 2.91 points in mean mAP. Visibility alone and activity delayed by one
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second remain near the audio baseline. However, person-resolved histories are
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weaker than aggregate histories and indistinguishable from histories whose
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identity continuity is shuffled. Thus the current evidence supports the value
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of timely local floor information, not a claim that person identity or track
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continuity has already been exploited.
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Voice Activity Projection (VAP) provides the broader future-activity view of
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turn taking \cite{ekstedt2022vap}. EgoSpeak's role-relative output preserves
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compatibility with that view, but its aggregate ``others'' channel discards
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whether the same or different visible people produced recent activity.
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Our oracle result shows that this discarded distinction is not automatically
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useful under the dense target: identity continuity must beat aggregate and
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shuffled controls before it enters the method claim.
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Moreover, conventional per-frame average precision can hide the behavioral
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failure of entering during an exchange between others. We therefore retain the
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dense EgoSpeak target while adding event evaluation of agent entry and yield;
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@@ -121,37 +136,40 @@ direct, continuous agent floor-action prediction and whether causal local
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evidence helps when the visible participant set changes.
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We call this task \emph{egocentric floor-action projection}. The study asks
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four questions: (RQ1) how accurately a frozen global omni state predicts the
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wearer-derived agent target and other-person activity; (RQ2) whether standard
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parameter-efficient tuning recovers missing performance; (RQ3) whether causal
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local audio and person-level visual evidence provide complementary
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information; and (RQ4) whether any aggregate gain reduces false agent entries
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without making the controller globally passive. EasyCom is suitable because
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four questions: (RQ1) how accurately a frozen global Omni state predicts the
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wearer-derived agent target and other-person activity; (RQ2) whether timely
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causal local audio and visible-person evidence complement that state; (RQ3)
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whether aggregate person-set evidence is sufficient or anonymous track
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continuity adds measurable value; and (RQ4) whether any dense gain reduces
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false agent entries without making the controller globally passive.
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Parameter-efficient tuning is a matched adaptation control rather than an
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assumed remedy. EasyCom is suitable because
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it provides synchronized egocentric audio--video, per-person tracks, and voice
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activity \cite{donley2021easycom}. Target-of-speech annotations, when used, are
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analysis strata only and are never model input or required output.
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The intended contributions are therefore: a controlled cross-backbone study
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of pretrained omni representations for EgoSpeak-style floor action; a
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lightweight local-evidence adaptation selected from
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pre-registered candidates; and a behavior-aligned event evaluation that maps
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wearer demonstrations to agent entry and yield decisions. Current
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Qwen2.5-Omni observations are motivation, not a claim that all omni models
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intrinsically fail. Likewise, track-consistent cross-attention becomes the
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final method only if it beats pooled, no-ID, and capacity-matched controls.
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The intended contributions are therefore: a controlled study of global Omni
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representations for EgoSpeak-style floor action; an oracle information audit
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that separates timely aggregate floor evidence from person continuity; a
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global--local adaptation selected from progressively structured candidates;
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and a behavior-aligned event evaluation that maps wearer demonstrations to
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agent entry and yield decisions. Current Qwen2.5-Omni observations are
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motivation, not a claim that all Omni models intrinsically fail. Likewise,
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track-consistent cross-attention becomes the final method only if it beats
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aggregate, shuffled/no-ID, and capacity-matched controls.
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\begin{figure}[t]
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\centering
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\fbox{\parbox[c][1.05in][c]{0.94\columnwidth}{\centering
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\todo{After model selection, draw the final system figure. For now it must show
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the shared experiment interface: raw causal AV; online face/head detection and
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causal tracking; backbone-specific global readout; recent audio and a masked
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set of anonymous track states; the gated local adapter; and the common
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$10\times3$ head. Mark causal cutoffs, trainable modules, parameter budgets,
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NULL/OFFSCREEN handling, and source-boundary resets.}}}
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\caption{Planned omni-model study for egocentric conversational floor action.
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The local adapter remains a candidate family until the controlled train-side
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comparison is complete.}
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\todo{After model selection, draw the final system figure. Show the shared
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interface: raw causal AV to a global Omni readout; a parallel recent-audio and
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visible-person path; aggregate/no-ID/track-organized variants; residual fusion;
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and the common $10\times3$ head. Draw the transcript-derived oracle only as a
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dashed, analysis-only upper-bound path. Mark causal cutoffs, provided versus
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online tracks, trainable modules, NULL/OFFSCREEN handling, and resets.}}}
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\caption{Global context and causal local evidence for egocentric floor action.
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Track organization is a controlled candidate, not a presupposed source of
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speaker identity.}
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\label{fig:method}
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\end{figure}
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@@ -207,13 +225,14 @@ expose a comparable causal state, report it as unsupported rather than inventing
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a non-equivalent readout. Add future backbones only before the experiment
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protocol is locked.}
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\subsection{Candidate local-evidence adaptation}
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\subsection{Global context and causal local evidence}
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The current hypothesis is that global omni states preserve broad semantic
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context but may make recent prosody, activity boundaries, and individual
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visual motion difficult for a shallow floor head to recover. From the most
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The global state $\vect g^{(m)}_t$ is responsible for broad scene and
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conversational context, but is not assumed to retain every localized cue needed
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for floor control. From the most
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recent $L_a$ seconds, a causal local audio encoder produces $\vect a_t$. At
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time $t$, an online detector and tracker produce a variable-size anonymous set
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time $t$, provided boxes during method isolation---and an online detector and
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tracker in the deployable condition---produce a variable-size anonymous set
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$\mathcal P_t=\{(\vect v_{t,i},\vect b_{t,i},\vect r_{t,i})\}_{i=1}^{N_t}$,
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where $\vect v_{t,i}$ is a crop feature, $\vect b_{t,i}$ is box geometry, and
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$\vect r_{t,i}$ contains only causal reliability variables such as visibility,
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@@ -231,8 +250,8 @@ current person set by masked cross-attention,
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W_q[\vect g^{(m)}_t;\vect a_t],
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[\vect h_{\varnothing};\vect h_{t,1};\ldots;\vect h_{t,N_t}]
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\right), \\
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\vect z^{(m)}_t &= \vect g^{(m)}_t+\tanh(\alpha)W_o\vect u_t,
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\qquad \alpha\vert_{\mathrm{init}}=0,
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\vect z^{(m)}_t &= \vect g^{(m)}_t+W_o\vect u_t,
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\qquad W_o\vert_{\mathrm{init}}=0,
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\label{eq:adapter}
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\end{align}
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where $\vect h_{\varnothing}$ is a learned NULL/OFFSCREEN token. Padding is
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@@ -243,14 +262,23 @@ reported. The operator is permutation equivariant
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\cite{lee2019settransformer}; temporary tracker IDs provide continuity, not
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identity semantics.
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Equation~\eqref{eq:track} is a candidate organization of local evidence, not a
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claim that recurrent identity is necessary. Simpler alternatives replace each
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$\vect h_{t,i}$ with a current-frame observation or pool the set into one
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aggregate vector. This distinction is important because the current oracle
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screen favors aggregate activity and does not separate correct from shuffled
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identity histories.
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This decomposition is informed by MuVAP: its global audio representation
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queries same-frame causal ASD track representations, followed by temporal
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modeling and gated global-to-speaker fusion \cite{qi2026muvap}. We retain the
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useful separation between global floor dynamics and person-grounded evidence,
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useful separation between global floor dynamics and person-organized evidence,
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but not its role-relative output: our fixed target is the invisible wearer's
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entry/yield action, not the next visible speaker. The zero-initialized gate
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also follows the conservative adapter principle used to inject visual evidence
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into strong audio models \cite{rouditchenko2024whisperflamingo}. Local evidence
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entry/yield action, not the next visible speaker. The zero-initialized residual
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output follows the conservative adapter principle used to inject visual
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evidence without perturbing the base prediction at initialization
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\cite{rouditchenko2024whisperflamingo}. Unlike a zero scalar gate, it permits
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the residual output layer to receive a gradient immediately. Local evidence
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is derived from the same causal raw media, not close microphones, transcripts,
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speaker labels, global identity anchors, or future frames.
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@@ -258,8 +286,10 @@ We evaluate candidates in increasing structural complexity: pooled recent
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audio/vision; a capacity-matched temporal branch; a per-frame person set with
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no cross-time identity; a shared track-wise temporal encoder; and person--audio
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cross-attention as in Eqs.~\eqref{eq:track}--\eqref{eq:adapter}. Only a
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candidate that improves the pre-registered event metric over simpler and
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capacity-matched controls becomes the final method. A limited latent
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candidate that improves the pre-registered event metric over simpler,
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aggregate, identity-shuffled, and capacity-matched controls becomes the final
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method. If person continuity does not separate from those controls, the final
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model remains a global-plus-local aggregate floor-evidence model. A limited latent
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bottleneck is tested only if large visible sets make full person attention a
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runtime bottleneck; it is not assumed to improve accuracy.
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@@ -339,6 +369,18 @@ clip-local anonymous participant tracks; its per-person voice coverage on the
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433-clip EgoSpeak split must be audited before reporting the same multi-other
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event analysis.
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\textbf{Oracle information audit.}
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Before selecting a learned local module, we measure what information could in
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principle complement the global state. Analysis-only sidecars expose
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transcript-derived speech activity no later than the current cutoff under six
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conditions: local audio, visibility only, one-second-delayed activity, timely
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aggregate visible activity, per-person histories, and histories with their
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cross-time identity assignments shuffled. These labels never enter a
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deployable model. The audit separates three hypotheses that ordinary feature
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ablation conflates: the value of seeing people, the value of knowing current
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visible-other activity, and the incremental value of preserving who produced
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that activity.
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\textbf{Backbone comparison.}
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The initial study covers Qwen2.5-Omni-3B, Qwen2.5-Omni-7B, and
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MiniCPM-o~4.5. For each backbone $m$, we first compare its frozen causal state
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@@ -383,9 +425,11 @@ confirmatory three-seed run.}
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For each backbone we compare: frozen global state $G_m$; PEFT $P_m$; $G_m$
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plus recent local audio; and $G_m$ plus pooled local audio--visual evidence.
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This compact matrix tests the representation hypothesis before investing in a
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complex fusion module. If local vision survives three seeds and the event
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gate, we then compare a parameter-matched temporal branch without person
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continuity, a separately trained per-frame/no-ID set branch, and a
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complex fusion module. The first learned target after the oracle audit is a
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causal estimator of timely aggregate visible-person floor evidence. Only if
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person-organized features survive three seeds, visual time/person corruptions,
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and the event gate do we compare a parameter-matched temporal branch without
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person continuity, a separately trained per-frame/no-ID set branch, and a
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track-consistent masked cross-attention branch. Provided-track and online-track
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inputs are reported separately. On a frozen track-aware checkpoint, a clip-consistent
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global renaming must leave outputs unchanged, whereas \emph{broken
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@@ -419,6 +463,36 @@ after the architecture is frozen.}
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\section{Results and Analysis}
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\label{sec:results}
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\begin{table}[t]
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\caption{Causal oracle-information screen on EasyCom development Session~12
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(seed 0, four epochs). Oracle speech activity is analysis-only. Values are
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percentages under the causal-valid protocol.}
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\label{tab:oracle}
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\centering
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\small
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\begin{tabular}{lcc}
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\hline
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Input condition & 0.2-s mAP & Mean mAP\\
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\hline
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Global + local audio & 72.58 & 58.77\\
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Visibility only & 71.95 & 58.86\\
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Activity delayed by 1 s & 72.02 & 58.90\\
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Aggregate visible activity & \textbf{79.55} & \textbf{61.68}\\
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Per-person activity histories & 78.80 & 61.11\\
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Identity-shuffled histories & 78.86 & 61.19\\
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\hline
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\end{tabular}
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\end{table}
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Table~\ref{tab:oracle} establishes an information opportunity, not a deployable
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result. Timely aggregate activity among visible non-wearers provides a large
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gain, while visibility alone and stale activity do not. However, preserving
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person-resolved history gives no advantage over destroying its cross-time
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identity assignment, and both trail the aggregate representation. The learned
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method must therefore first recover useful local floor evidence; person-track
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continuity is retained only if subsequent no-ID and broken-track controls
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separate.
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\begin{table}[t]
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\caption{Exploratory Qwen2.5-Omni-3B local-branch evidence on EasyCom test
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Sessions 1--3. Values are percentages from one seed, not a cross-backbone or
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@@ -441,9 +515,9 @@ $\Delta$ visual & +0.30 & +0.02 & +0.29\\
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Table~\ref{tab:preliminary} shows why aggregate mAP alone is insufficient.
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Pooled vision gives a small gain, while immediate wearer AP is nearly
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unchanged. This is compatible with either weak but useful social grounding or
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generic visual regularization; only matched-recall event evaluation and
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track-continuity controls can distinguish them.
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unchanged. This is compatible with either useful generic local context or
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regularization; it is not evidence of person grounding. Only matched-recall
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event evaluation and visual-alignment controls can distinguish these cases.
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A separate Qwen-3B dense-cache diagnostic gave 58.16 mean mAP for its frozen
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readout and 56.20 for one LoRA recipe. Because that diagnostic used a different
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feature protocol, it is not combined numerically with
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@@ -522,10 +596,11 @@ rejected PEFT recipes and fusion candidates to supplementary material unless
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they directly explain the selected method.}
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\textbf{Qualitative evidence.}
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For a multi-other exchange, visualize per-person speech activity and track IDs,
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wearer ground truth, the frozen-global and selected-local wearer-entry scores,
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and the single frozen threshold on one physical time axis. If the selected
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candidate is track-aware, also show its broken-continuity score. A useful
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For a multi-other exchange, visualize annotation-derived per-person activity
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as an analysis reference, provided track IDs when applicable, wearer ground
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truth, the frozen-global and selected-local wearer-entry scores, and the single
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frozen threshold on one physical time axis. If the selected candidate is
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track-aware, also show its broken-continuity score. A useful
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example shows the frozen baseline rising at an other-speaker boundary while
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the selected adapter remains below threshold; a companion positive example
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must show that a real wearer onset is not suppressed.
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@@ -541,17 +616,21 @@ event result and cannot establish it alone.}
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\label{sec:conclusion}
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We study when an egocentric agent should enter or yield a multiparty floor, not
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merely whether someone will speak. The central question is model-agnostic:
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whether frozen or parameter-efficiently adapted omni representations expose
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the fine-grained floor cues required by a 5-Hz controller, and whether causal
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local evidence closes any gap. Dense activity forecasting supplies a common
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target, while matched-recall event evaluation tests whether an apparent gain
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actually prevents intrusions during multi-other exchanges. Current Qwen-3B
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results are exploratory motivation only. \todo{After the controlled study,
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state which backbone/adapter was selected, whether the representation pattern
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generalized beyond Qwen, the quantitative false-entry and onset/yield results,
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and the main deployment limitation. Do not infer success from aggregate mAP or
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selected examples alone.}
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merely whether someone will speak. The working decomposition is global Omni
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context plus causal local audiovisual floor evidence. The current
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Qwen2.5-Omni-3B oracle audit supports the second term: timely aggregate
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visible-other activity is informative beyond the global state and recent
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mixed audio. It does not support the stronger claim that participant identity
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or track continuity adds value, because per-person histories do not beat an
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identity-shuffled control. Dense activity forecasting supplies a comparable
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target, while matched-recall event evaluation must determine whether a learned
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local estimator actually prevents intrusions during multi-other exchanges
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without suppressing valid wearer entry or yield. \todo{After the controlled
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study, state which learned local variant was selected, how much of the oracle
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gap it recovered, whether the pattern generalized beyond Qwen, the
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quantitative false-entry and onset/yield results, and the main deployment
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limitation. If no learned variant passes these tests, conclude with the
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information audit rather than claiming a track-based solution.}
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\bibliographystyle{IEEEbib}
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\bibliography{references}
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Xin Wang