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.
@article{arxiv.2602.18618,
title = {Narrating For You: Prompt-guided Audio-visual Narrating Face Generation Employing Multi-entangled Latent Space},
author = {Aashish Chandra and Aashutosh A and Abhijit Das},
journal= {arXiv preprint arXiv:2602.18618},
year = {2026}
}
Comments
To appear in the Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026. Presented at Poster Session 1