Facial Parameter Splicing: A Novel Approach to Efficient Talking Face Generation
Xianhao Chen, Kuan Chen, Yuanling Mao, Linna Zhou, Weike You · 2023
In recent years, generating talking faces has become a popular research area due to their applications in various fields. However, most current models require high computational demands, which limits their practicality. To address this issue, some researchers have developed phoneme-face indexes to generate talking videos quickly and efficiently. But when the training video is too short, it is not possible to create mappings for all phonemes. To overcome this limitation, we introduced a large-scale phoneme-face dictionary to complete the feature mapping, designed a novel method for fast phoneme-face indexes search and trained a generative adversarial network (GAN) to generate video from phoneme-face sequences. Our proposed method is capable of completing the phoneme-face mapping using less than 10 seconds training video of the target person based on the large-scale dictionary and fast search algorithm and reducing the preprocessing and training time for talking videos generation.