Neural network for speech denoising trained with deep feature losses
US10726858B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 18, 2018 |
| Grant date | Jul 28, 2020 |
| Priority date | — |
| Expiry date | Jan 19, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are provided for speech denoising using a denoising neural network (NN) trained with deep feature losses obtained from an audio classifier NN. A methodology implementing the techniques according to an embodiment includes applying the speech denoising NN, to be trained, to a noisy sample of a training speech signal to generate a processed training speech signal. The method further includes applying a trained audio classifier NN to the processed training speech signal to generate a first set of activation features, and applying the trained audio classifier NN to a clean sample of the training speech signal to generate a second set of activation features. The method further includes calculating a loss value based on the first and second sets of activation features, and performing a back-propagation training update of the denoising NN, based on the loss value. The method includes iterating this process to further train the denoising NN.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.