The UEA Digital Humans entry to the GENEA Challenge 2023

Abstract

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 speech of both the main-agent and an interlocutor. We adapt a Transformer-XL architecture for this task by adding a cross-attention module that integrates the interlocutor’s speech with that of the main-agent. Our model is conditioned on speech audio (encoded using PASE+), text (encoded using FastText) and a speaker identity label, and is able to generate smooth and speech appropriate gestures for a given identity. We consider the GENEA Challenge user study results and present a discussion of our model strengths and where improvements can be made.