日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
ヒューマノイド/マルチモーダル対話arXiv:2610.06153

話し、描き、演じる:会話型ヒューマノイドロボットのための同期音声と社会的ジェスチャー・デジタル顔の統合

Talk, Render, Act: Integrating Social Gesture and Digital Face with Synchronized Speech for Conversational Humanoid Robot

シェア:XThreadsFacebookLINEはてブBluesky

音声・顔アニメーション・身体ジェスチャーを統合し、意味的に一貫した応答をリアルタイムで生成するエージェント型フレームワークTRABotを提案し、G1ヒューマノイドで実装した。

著者: Jin Jiang, Kun Li, Jiancong Ma, Shengcai Liao

分類: cs.RO

原文アブストラクト

Expressive humanoid interaction requires speech, facial animation, and body gestures to form a coherent response. However, many full-body humanoid robots produce speech and gestures without a visually expressive face, while talking-face animation and robot gesture generation are typically developed separately. We present Talk, Render, Act (TRABot), an agent-based framework comprising specialized agents for motion-atom construction, dialogue generation, motion planning, and facial animation. First, to produce natural and semantically meaningful gestures, we construct Robot-Ready Semantic Motion Atoms by segmenting long-form, G1-retargeted BEAT2 motion into units with natural gesture boundaries, human-verified communicative functions, and feasible trajectories. Second, to preserve semantic order and coordinate body motion with the spoken response, we introduce a Semantic-Conditioned Compositional Planner. Given an ordered semantic function sequence and an estimated response duration, the planner selects approved atoms to realize the longest feasible action sequence while accounting for transitions and neutral recovery. Finally, we deploy a Streaming Face-Speech-Body Integration system on a physical G1 humanoid, combining streaming dialogue audio, audio-driven facial animation, and semantically planned body motion in a unified real-time interaction loop. Quantitative and qualitative experiments demonstrate that TRAbot achieves the best overall performance among all compared conditions in terms of naturalness, expressiveness, and multimodal coherence.

PR本紙発行元 EmplifAI