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Automatic DJ Transitions with Differentiable Audio Effects and Generative Adversarial Networks.

, , , , , and . ICASSP, page 466-470. IEEE, (2022)

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Differentiable Signal Processing With Black-Box Audio Effects., , , and . ICASSP, page 66-70. IEEE, (2021)Distortion Audio Effects: Learning How to Recover the Clean Signal., , , , , and . ISMIR, page 218-225. (2022)A general-purpose deep learning approach to model time-varying audio effects., , and . CoRR, (2019)Deep learning for audio effects modeling.. Queen Mary University of London, UK, (2021)British Library, EThOS.Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects., , , , , and . ICASSP, page 1-5. IEEE, (2023)Automatic music mixing with deep learning and out-of-domain data., , , , , and . ISMIR, page 411-418. (2022)Ensemble Models for Spoofing Detection in Automatic Speaker Verification., , , , , and . INTERSPEECH, page 1018-1022. ISCA, (2019)VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance., , , , , , and . ICASSP, page 596-600. IEEE, (2024)Modeling Nonlinear Audio Effects with End-to-end Deep Neural Networks., and . ICASSP, page 171-175. IEEE, (2019)Automatic DJ Transitions with Differentiable Audio Effects and Generative Adversarial Networks., , , , , and . ICASSP, page 466-470. IEEE, (2022)