Year: 2023
Type: preprint
Abstract: This short paper introduces a workflow for generating realistic soundscapes for visual media. In contrast to prior work, which primarily focus on matching sounds for on-screen visuals, our approach extends to suggesting sounds that may not be immediately visible but are essential to crafting a convincing and immersive auditory environment. Our key insight is leveraging the reasoning capabilities of language models, such as ChatGPT. In this paper, we describe our workflow, which includes creating a scene context, brainstorming sounds, and generating the sounds.
Source: arXiv (Cornell University)
Authors: Lin, David Chuan-En, Martelaro, Nikolas
Institution: Carnegie Mellon University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4388585694