# Text/Speech-Driven Full-Body Animation

arXiv: https://arxiv.org/abs/2205.15573 · HTML: https://mlsanity.com/paper/2205.15573/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 May 2022.

## Built on by (most cited first, 3 of 3)

- [A Comprehensive Review of Data-Driven Co-Speech Gesture Generation](https://mlsanity.com/paper/2301.05339/) (2023)
- [AQ-GT: a Temporally Aligned and Quantized GRU-Transformer for Co-Speech Gesture Synthesis](https://mlsanity.com/paper/2305.01241/) (2023)
- [Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent](https://mlsanity.com/paper/2311.12804/) (2023)

## Abstract (arXiv)

Due to the increasing demand in films and games, synthesizing 3D avatar animation has attracted much attention recently. In this work, we present a production-ready text/speech-driven full-body animation synthesis system. Given the text and corresponding speech, our system synthesizes face and body animations simultaneously, which are then skinned and rendered to obtain a video stream output. We adopt a learning-based approach for synthesizing facial animation and a graph-based approach to animate the body, which generates high-quality avatar animation efficiently and robustly. Our results demonstrate the generated avatar animations are realistic, diverse and highly text/speech-correlated.