Playing For You: Text Prompt-guided Joint Audio-visual Generation for Narrating Faces using Multi-entangled Latent Space

Aashish Chandra, Aashutosh A V, Sk Aziz Ali, Abhijit Das

Keywords: Generating Multimoda

Abstract:

We present a novel approach for generating realistic speaking and taking 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, a driving image and the voice profile of an individual and then combines them to pass it to the multi-entangled latent space to foster key-vale and query for 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. Our experiments and analysis through standard metrics showcase the effectiveness of our model. All model checkpoints, code and the proposed dataset can be found at: https://github.com/Playing-for-you.

Primary Area: applications to computer vision, audio, language, and other modalities

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Submission Number: 10887