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Speech-driven facial animation with spectral gathering and temporal attention

Frontiers of Computer Science volume 16, Article number: 163703 (2022) Cite this article

Abstract

In this paper, we present an efficient algorithm that generates lip-synchronized facial animation from a given vocal audio clip. By combining spectral-dimensional bidirectional long short-term memory and temporal attention mechanism, we design a light-weight speech encoder that learns useful and robust vocal features from the input audio without resorting to pre-trained speech recognition modules or large training data. To learn subject-independent facial motion, we use deformation gradients as the internal representation, which allows nuanced local motions to be better synthesized than using vertex offsets. Compared with state-of-the-art automatic-speech-recognition-based methods, our model is much smaller but achieves similar robustness and quality most of the time, and noticeably better results in certain challenging cases.

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Acknowledgements

We would like to thank VOCA group for publishing their database. This work was partially supported by the National Key Research & Development Program of China (2016YFB1001403) and the National Natural Science Foundation of China (Grant No. 61572429).

Author information

Authors and Affiliations

  1. State Key Lab of CAD&CG, Zhejiang University, Hangzhou, 310058, China

    Yujin Chai, Yanlin Weng & Kun Zhou

  2. FaceUnity Technology Inc., Hangzhou, 310011, China

    Lvdi Wang

Authors
  1. Yujin Chai
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  2. Yanlin Weng
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  3. Lvdi Wang
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  4. Kun Zhou
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Corresponding author

Correspondence to Yanlin Weng.

Additional information

Yujin Chai received his BS degree in the Computer Science and Technology Department from Zhejiang University, China in 2016. He is now a PhD student at the State Key Lab of CAD&CG, Zhejiang University. His research interests include machine learning and facial animation.

Yanlin Weng is currently an associate professor of the School of Computer Science and Technology at Zhejiang University, China. She got her PhD degree in computer science from University of Wisconsin — Milwaukee, USA and her master’s and bachelor’s degrees in control science and engineering from Zhejiang University. Her research interests include computer graphics and multimedia.

Lvdi Wang is currently the Director of FaceUnity Research Center of Beijing, China. He received his PhD degree in computer science from Institute for Advanced Study, Tsinghua University, China in 2011, under the supervision of Professor Baining Guo. After that, he has spent four years at Microsoft Research Asia and two years at Apple Inc. His works focus on computer graphics, speech, and natural language processing techniques.

Kun Zhou is a professor in the Computer Science Department of Zhejiang University, and the Director of the State Key Lab of CAD&CG, China. Prior to joining Zhejiang University in 2008, Dr. Zhou was a leader researcher of the Internet Graphics Group at Microsoft Research Asia. He received his BS degree and PhD degree in computer science from Zhejiang University in 1997 and 2002, respectively. His research interests are in visual computing, parallel computing, human computer interaction, and virtual reality. He is a Fellow of IEEE.

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Chai, Y., Weng, Y., Wang, L. et al. Speech-driven facial animation with spectral gathering and temporal attention. Front. Comput. Sci. 16, 163703 (2022). https://doi.org/10.1007/s11704-020-0133-7

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