为你叙述：基于多纠缠潜在空间的提示引导音频视觉叙述面部生成
Narrating For You: Prompt-guided Audio-visual Narrating Face Generation Employing Multi-entangled Latent Space
AI总结：
本文提出了一种基于多纠缠潜在空间的音频视觉叙述面部生成方法，通过合成静态图像、语音档案和目标文本来生成逼真的说话面孔。
摘要：
我们提出了一种新的方法，通过从静态图像、语音档案和目标文本合成一个人的语音和面部动作来生成逼真的说话和谈话面孔。该模型编码提示/驱动文本、驱动图像和个体的语音档案，然后将它们结合起来，传递到多纠缠潜在空间，以促进音频和视频模态生成管道中的键值对和查询。多纠缠潜在空间负责在模态之间建立时空个性化特征。进一步地，纠缠特征被传递到每个模态的相应解码器中，以生成输出音频和视频。
英文摘要：
We present a novel approach for generating realistic speaking and talking faces by synthesizing a person's voice and facial movements from a static image, a voice profile, and a target text. The model encodes the prompt/driving text, the driving image, and the voice profile of an individual and then combines them to pass them to the multi-entangled latent space to foster key-value pairs and queries for the audio and video modality generation pipeline. The multi-entangled latent space is responsible for establishing the spatiotemporal person-specific features between the modalities. Further, entangled features are passed to the respective decoder of each modality for output audio and video generation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
