Generative adversarial network based audio restoration
US12001950B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 12, 2019 |
| Grant date | Jun 4, 2024 |
| Priority date | — |
| Expiry date | Apr 4, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L21/0208
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Mechanisms are provided for implementing a generative adversarial network (GAN) based restoration system. A first neural network of a generator of the GAN based restoration system is trained to generate an artificial audio spectrogram having a target damage characteristic based on an input audio spectrogram and a target damage vector. An original audio recording spectrogram is input to the trained generator, where the original audio recording spectrogram corresponds to an original audio recording and an input target damage vector. The trained generator processes the original audio recording spectrogram to generate an artificial audio recording spectrogram having a level of damage corresponding to the input target damage vector. A spectrogram inversion module converts the artificial audio recording spectrogram to an artificial audio recording waveform output.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.