Neural network-based speech processing
US9324320B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 2, 2014 |
| Grant date | Apr 26, 2016 |
| Priority date | — |
| Expiry date | Oct 2, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L17/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Pairs of feature vectors are obtained that represent speech. Some pairs represent two samples of speech from the same speakers, and other pairs represent two samples of speech from different speakers. A neural network feeds each feature vector in a sample pair into a separate bottleneck layer, with a weight matrix on the input of both vectors tied to one another. The neural network is trained using the feature vectors and an objective function that induces the network to classify whether the speech samples come from the same speaker. The weights from the tied weight matrix are extracted for use in generating derived features for a speech processing system that can benefit from features that are thus transformed to better reflect speaker identity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.