Smooth-Foley: Creating Continuous Sound for Video-to-Audio Generation Under Semantic Guidance
Yaoyun Zhang, Xuenan Xu, Mengyue Wu

TL;DR
Smooth-Foley is a novel video-to-audio generation model that uses semantic guidance from text to improve audio-video alignment and produce continuous, high-quality Foley sounds, especially in challenging scenarios with moving visuals.
Contribution
It introduces a semantic-guided generative model with specialized adapters to enhance temporal and semantic alignment in video-to-audio synthesis.
Findings
Outperforms existing models in continuous sound scenarios
Achieves higher quality and better physical law adherence
Improves semantic and temporal alignment in audio generation
Abstract
The video-to-audio (V2A) generation task has drawn attention in the field of multimedia due to the practicality in producing Foley sound. Semantic and temporal conditions are fed to the generation model to indicate sound events and temporal occurrence. Recent studies on synthesizing immersive and synchronized audio are faced with challenges on videos with moving visual presence. The temporal condition is not accurate enough while low-resolution semantic condition exacerbates the problem. To tackle these challenges, we propose Smooth-Foley, a V2A generative model taking semantic guidance from the textual label across the generation to enhance both semantic and temporal alignment in audio. Two adapters are trained to leverage pre-trained text-to-audio generation models. A frame adapter integrates high-resolution frame-wise video features while a temporal adapter integrates temporal…
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Taxonomy
TopicsMusic Technology and Sound Studies · Music and Audio Processing
MethodsSoftmax · Attention Is All You Need · Adapter
