ICMI-MLMI

This paper describes a system developed for the GENEA (Generation and Evaluation of Non-verbal Behaviour for Embodied Agents) Challenge 2023. Our solution builds on an existing diffusion-based motion synthesis model. We propose a contrastive speech and ...

Human communication relies on multiple modalities such as verbal expressions, facial cues, and bodily gestures. Developing computational approaches to process and generate these multimodal signals is critical for seamless human-agent interaction. A ...

This paper presents the CASIA-GO entry to the Generation and Evaluation of Non-verbal Behaviour for Embedded Agents (GENEA) Challenge 2023. The system is originally designed for few-shot scenarios such as generating gestures with the style of any in-the-...

In this paper, we introduce the DiffuseStyleGesture+, our solution for the Generation and Evaluation of Non-verbal Behavior for Embodied Agents (GENEA) Challenge 2023, which aims to foster the development of realistic, automated systems for generating ...

This paper describes FineMotion’s entry to the GENEA Challenge 2023. We explore the potential of DeepPhase embeddings by adapting neural motion controllers to conversational gesture generation. This is achieved by introducing a recurrent encoder for ...

This paper reports on the GENEA Challenge 2023, in which participating teams built speech-driven gesture-generation systems using the same speech and motion dataset, followed by a joint evaluation. This year’s challenge provided data on both sides of a ...

This paper describes our entry to the GENEA (Generation and Evaluation of Non-verbal Behaviour for Embodied Agents) Challenge 2023. This year’s challenge focuses on generating gestures in a dyadic setting – predicting a main-agent’s motion from the ...