It Takes Two: Real-time Co-Speech Two-person's Interaction Generation via Reactive Auto-regressive Diffusion Model

• URL: http://arxiv.org/abs/2412.02419v1
• Date: Tue, 03 Dec 2024 12:31:44 GMT
• Title: It Takes Two: Real-time Co-Speech Two-person's Interaction Generation via Reactive Auto-regressive Diffusion Model
• Authors: Mingyi Shi, Dafei Qin, Leo Ho, Zhouyingcheng Liao, Yinghao Huang, Junichi Yamagishi, Taku Komura,
• Abstract summary: We introduce an audio-driven, auto-regressive system designed to synthesize dynamic movements for two characters during a conversation. To the best of our knowledge, this is the first system capable of generating interactive full-body motions for two characters from speech in an online manner.
• Score: 34.94330722832987
• License:
• Abstract: Conversational scenarios are very common in real-world settings, yet existing co-speech motion synthesis approaches often fall short in these contexts, where one person's audio and gestures will influence the other's responses. Additionally, most existing methods rely on offline sequence-to-sequence frameworks, which are unsuitable for online applications. In this work, we introduce an audio-driven, auto-regressive system designed to synthesize dynamic movements for two characters during a conversation. At the core of our approach is a diffusion-based full-body motion synthesis model, which is conditioned on the past states of both characters, speech audio, and a task-oriented motion trajectory input, allowing for flexible spatial control. To enhance the model's ability to learn diverse interactions, we have enriched existing two-person conversational motion datasets with more dynamic and interactive motions. We evaluate our system through multiple experiments to show it outperforms across a variety of tasks, including single and two-person co-speech motion generation, as well as interactive motion generation. To the best of our knowledge, this is the first system capable of generating interactive full-body motions for two characters from speech in an online manner.

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