Abstract
The modern deep neural network has allowed an applicable level of speech-driven facial animation, simulating natural and precise 3D animation from speech data. Regardless, many of the works show weakness in drastic emotional expression and flexibility of the animation. In this work, we introduce emotion guided speech-driven facial animation, simultaneously proceeding with classification and regression from the speech data to generate a controllable level of evident emotional expression on facial animation. Performance using our method shows reasonable expressiveness of facial emotion with controllable flexibility. Extensive experiments indicate that our method generates more expressive facial animation with controllable flexibility compared to previous approaches.
Author supplied keywords
Cite
CITATION STYLE
Chun, S., Choe, D., Kang, S., An, S., Jo, Y., & Oh, I. (2021). Emotion Guided Speech-Driven Facial Animation. In Proceedings - SIGGRAPH Asia 2021 Posters, SA 2021. Association for Computing Machinery, Inc. https://doi.org/10.1145/3476124.3488649
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.