Evaluation of Real-Time Aliasing Reduction Methods in Neural Networks for Nonlinear Audio Effects Modelling
hal.structure.identifier | Université de Bordeaux [UB] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Orosys | |
hal.structure.identifier | Méthodes avancées d’apprentissage statistique et de contrôle [ASTRAL] | |
dc.contributor.author | VANHATALO, Tara | |
hal.structure.identifier | Université de Bordeaux [UB] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Méthodes avancées d’apprentissage statistique et de contrôle [ASTRAL] | |
dc.contributor.author | LEGRAND, Pierrick | |
hal.structure.identifier | Studio de Création et de Recherche en Informatique et Musique Électroacoustique [SCRIME] | |
hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
dc.contributor.author | DESAINTE-CATHERINE, Myriam | |
hal.structure.identifier | Image et Son | |
hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
dc.contributor.author | HANNA, Pierre | |
hal.structure.identifier | Orosys | |
dc.contributor.author | PILLE, Guillaume | |
dc.date.issued | 2023-10-09 | |
dc.identifier.issn | 0004-7554 | |
dc.description.abstractEn | Neural networks have seen increased popularity in recent years for nonlinear audio effects modelling. Such a task requires sampling and creates high frequency harmonics that can quickly surpass the Nyquist rate, creating aliasing in the baseband. In this work, we study the impact of processing audio with neural networks and the potential aliasing these highly nonlinear algorithms can incur or aggravate. Namely, we evaluate the performance of a number of anti-aliasing methods for use in real-time. Notably, one method of anti-aliasing capable of real-time performance was identified: forced sparsity through network pruning. | |
dc.language.iso | en | |
dc.publisher | Audio Engineering Society | |
dc.rights.uri | http://creativecommons.org/licenses/by/ | |
dc.subject.en | Aliasing reduction | |
dc.subject.en | neural networks | |
dc.subject.en | nonlinear audio effects modelling | |
dc.subject.en | real-time | |
dc.title.en | Evaluation of Real-Time Aliasing Reduction Methods in Neural Networks for Nonlinear Audio Effects Modelling | |
dc.type | Article de revue | |
dc.identifier.doi | 10.17743/jaes.2022.0122 | |
dc.subject.hal | Informatique [cs] | |
dc.subject.hal | Informatique [cs] | |
dc.subject.hal | Mathématiques [math] | |
dc.subject.hal | Science non linéaire [physics] | |
bordeaux.journal | Journal of the Audio Engineering Society | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-04235385 | |
hal.version | 1 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-04235385v1 | |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal%20of%20the%20Audio%20Engineering%20Society&rft.date=2023-10-09&rft.eissn=0004-7554&rft.issn=0004-7554&rft.au=VANHATALO,%20Tara&LEGRAND,%20Pierrick&DESAINTE-CATHERINE,%20Myriam&HANNA,%20Pierre&PILLE,%20Guillaume&rft.genre=article |
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