Prompt-guided Precise Audio Editing with Diffusion Models
<|reference_start|>Prompt-guided Precise Audio Editing with Diffusion Models: 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.<|reference_end|>
@article{xu2024prompt-guided,
    title={Prompt-guided Precise Audio Editing with Diffusion Models},
    author={Manjie Xu, Chenxing Li, Duzhen zhang, Dan Su, Wei Liang, Dong Yu},
    journal={arXiv preprint arXiv:2406.04350},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.04350},
    primaryClass={cs.SD cs.AI cs.LG eess.AS}
}