Faces that Speak: Jointly Synthesising Talking Face and Speech from Text

Youngjoon Jang, Ji-Hoon Kim, Junseok Ahn, Doyeop Kwak, Hong-Sun Yang, Yoon-Cheol Ju, Il-Hwan Kim, Byeong-Yeol Kim, Joon Son Chung; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 8818-8828

The goal of this work is to simultaneously generate natural talking faces and speech outputs from text. We achieve this by integrating Talking Face Generation (TFG) and Text-to-Speech (TTS) systems into a unified framework. We address the main challenges of each task: (1) generating a range of head poses representative of real-world scenarios and (2) ensuring voice consistency despite variations in facial motion for the same identity. To tackle these issues we introduce a motion sampler based on conditional flow matching which is capable of high-quality motion code generation in an efficient way. Moreover we introduce a novel conditioning method for the TTS system which utilises motion-removed features from the TFG model to yield uniform speech outputs. Our extensive experiments demonstrate that our method effectively creates natural-looking talking faces and speech that accurately match the input text. To our knowledge this is the first effort to build a multimodal synthesis system that can generalise to unseen identities.