DuplexAvatar: Unified 3D Motion Understanding and Generation for Full-Duplex Spoken Dialogue

An interactive avatar must understand behavioral context and generate appropriate 3D motion during real-time spoken interaction. This requires behavioral understanding, multimodal response generation, and motion realization to operate within a shared conversational state. We introduce DuplexAvatar, a unified full-duplex speech–language–motion model that maintains speech, language, behavior plans, and holistic 3D motion within a shared causal state, supporting both behavior understanding and multimodal response generation. At the core of DuplexAvatar is the Executable Behavior Plan, a structured and executable representation of behavioral intent that specifies what to do, where and when it applies, and what must remain unchanged. The plan connects semantic decisions to controllable motion realization and provides an explicit interface for localized intervention. Structured operations are executed by a typed executor, while open-ended requests are realized through masked residual flow. Before commitment, geometry-based checks and motion-only readback can trigger a bounded local correction; only uncommitted future motion remains revisable, while committed motion is re-encoded into the conversational state. We further compile Spear, a multi-source, multi-view supervision suite that provides motion events, executable plans, geometry-grounded queries, and controlled counterfactual edits, together with an intervention-based benchmark for controllable behavior realization. Experiments under matched evaluation settings show consistent improvements across speech-conditioned motion generation, motion understanding, and behavioral control, achieving 73% human preference, 91.8% Event F1, and 78.95% constraint success. Together, DuplexAvatar and Spear provide an inspectable path from behavioral intent to realized 3D motion within full-duplex spoken interaction.