Video AvatarsBehavior & Expressiveness

Axis 2 — Avatar Behavior & Expressiveness

Going beyond lip-sync: behavioral extraction, coherent body language, expressive TTS, and latency optimization.

The system strictly separates video source analysis (Stream A, offline, non-critical) from avatar construction (Stream B, main R&D). Avatar training video is never played in the experience. The Axis 2 challenge is making Stream B fast enough to meet the Axis 1 latency budget.

Stream A: Video analysis — offline, non-criticalStream B: Avatar construction — main R&D challenge (Axis 2b)
STREAM A — Source Video AnalysisOffline processing · Not a major R&D challengeVideo Archives(source material)✓ Offline · SimpleFrameExtractionJPEG · 1fpsSemanticAnalysisCLIP · BLIP2Tags · EmbeddingsVideoDescriptor DBVector DBSemantic searchDynamic VideoPlaylistUpdated in real-timebased on conversationIllustrative VideosPlay alongside avatar(secondary stream)Avatar speaks ✓Informative / Interview VideosAvatar pausesvideo delivers spoken contentAvatar pauses ⏸STREAM B — Avatar ConstructionOffline training + real-time inference · Main R&D challengeTrainingVideoSingle · Never playedin the experienceBehavioralFingerprintMicro-expressionsGestures · RhythmProsodyAvatarModel⚠ R&D Challenge (Axis 2b)Diffusion distillationIntelligent cache<500ms targetReal-timeAvatarSpeaks · Pauses duringinformative videosOUTPUT — Dual-Stream ExperienceMulti-stream sync · <100ms · Memoways internal expertiseMain StreamReal-time avatarWebRTC · H.264 · <100msPauses during informative videosSecondary StreamDynamic video playlistIllustrative: insert alongside avatarInformative: full-screen, avatar pausesSmart orchestration: avatar yields to informative videosIllustrative videos play as inserts without interrupting avatarResearch Axes: Axis 2b (Avatar <500ms) · Axis 2a (Expressive TTS) · Axis 1 (Conversational Memory)Source video analysis (Stream A) is NOT a research challenge — standard offline processing
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AXE 22A

Behavioral Extraction from Archives

Extract individual behavioral patterns from existing videos — without new capture sessions. Identify: micro-expression repertoire, gestural vocabulary, gesture-speech temporal relationships, postural habits.

Key question:

Can we automatically extract an individual's gestural vocabulary from uncontrolled footage?

AXE 22B

Coherent Body Language Generation

Go beyond lip-sync. Generate coordinated body behavior: synchronized with speech content and emotional tone, culturally appropriate, consistent with the defined personality.

Key question:

Most current systems focus on the face only. The body is absent or from a template library.

AXE 22C

Personalized Expressive TTS

Generate speech capturing not only vocal timbre but the prosodic fingerprint: rhythm, emphasis patterns, pause distribution, emotional modulation. The voice must match the avatar's emotional state.

Key question:

How much source audio is needed to capture prosodic individuality? Minutes or hours?

AXE 22D

Cost / Quality / Latency Optimization

Approaches: pre-rendered base + real-time lip-sync, model distillation, intelligent cache, graceful degradation. The goal is an acceptable personalized avatar at <500ms on accessible hardware.

Key question:

What is the minimum compute for acceptable personalized avatar generation at <500ms?