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Real-time Gesture Animation Generation from Speech for Virtual Human Interaction

2022-08-05 15:56:34
Manuel Rebol, Christian Gütl, Krzysztof Pietroszek
arXiv_CV
               
Abstract

We propose a real-time system for synthesizing gestures directly from speech. Our data-driven approach is based on Generative Adversarial Neural Networks to model the speech-gesture relationship. We utilize the large amount of speaker video data available online to train our 3D gesture model. Our model generates speaker-specific gestures by taking consecutive audio input chunks of two seconds in length. We animate the predicted gestures on a virtual avatar. We achieve a delay below three seconds between the time of audio input and gesture animation. Code and videos are available at this https URL

Abstract (translated)

URL

https://arxiv.org/abs/2208.03244

PDF

https://arxiv.org/pdf/2208.03244.pdf

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