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ECHO-G is a new framework that generates full-body co-speech motion for humanoid robots by jointly conditioning on speech audio and timed transcripts. Its Speech-Grounded Diffusion Transformer (SGDiT) integrates acoustic features with linguistic context to coordinate speech prosody, content, and em...
ECHO-G is a new framework that generates full-body co-speech motion for humanoid robots by jointly conditioning on speech audio and timed transcripts. Its Speech-Grounded Diffusion Transformer (SGDiT) integrates acoustic features with linguistic context to coordinate speech prosody, content, and em...
AI-assisted summary based on the listed source.
Generating full-body co-speech motion for humanoid robots requires coordinating speech prosody, linguistic content, and embodiment-specific motion. To this end, we present ECHO-G, a framework jointly conditioned on speech audio and timed transcripts. Its Speech-Grounded Diffusion Transformer (SGDiT) combines...
Coordinating speech and motion in humanoid robots is complex due to differing granularities of audio and language data. ECHO-G's approach could improve naturalistic robot interactions by better synchronizing speech and body movements.
Hardware and robotics watchers may want to track whether this becomes a product, benchmark, or deployment signal.
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