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arXiv · 2406.04350

Prompt-guided Precise Audio Editing with Diffusion Models

Manjie Xu·Chenxing Li·Duzhen zhang·Dan Su·Wei Liang·Dong Yu
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Abstract

Audio editing involves the arbitrary manipulation of audio content through precise control. Although text-guided diffusion models have made significant advancements in text-to-audio generation, they still face challenges in finding a flexible and precise way to modify target events within an audio track. We present a novel approach, referred to as PPAE, which serves as a general module for diffusion models and enables precise audio editing. The editing is based on the input textual prompt only and is entirely training-free. We exploit the cross-attention maps of diffusion models to facilitate accurate local editing and employ a hierarchical local-global pipeline to ensure a smoother editing process. Experimental results highlight the effectiveness of our method in various editing tasks.

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Manjie Xu, Chenxing Li, Duzhen zhang, Dan Su, Wei Liang, Dong Yu. 2024-05-11. Prompt-guided Precise Audio Editing with Diffusion Models. https://arxiv.org/abs/2406.04350

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