Z-vectors: speaker embeddings from raw audio using sincnet, extended CNN architecture and in-network augmentation techniques
US11715460B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2020 |
| Grant date | Aug 1, 2023 |
| Priority date | — |
| Expiry date | Oct 8, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04M3/5166
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are systems and methods for improved audio analysis using a computer-executed neural network having one or more in-network data augmentation layers. The systems described herein help ease or avoid unwanted strain on computing resources by employing the data augmentation techniques within the layers of the neural network. The in-network data augmentation layers will produce various types of simulated audio data when the computer applies the neural network on an inputted audio signal during a training phase, enrollment phase, and/or testing phase. Subsequent layers of the neural network (e.g., convolutional layer, pooling layer, data augmentation layer) ingest the simulated audio data and the inputted audio signal and perform various operations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.