Learning front-end speech recognition parameters within neural network training
US10360901B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2014 |
| Grant date | Jul 23, 2019 |
| Priority date | — |
| Expiry date | Apr 15, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for learning front-end speech recognition parameters as part of training a neural network classifier include obtaining an input speech signal, and applying front-end speech recognition parameters to extract features from the input speech signal. The extracted features may be fed through a neural network to obtain an output classification for the input speech signal, and an error measure may be computed for the output classification through comparison of the output classification with a known target classification. Back propagation may be applied to adjust one or more of the front-end parameters as one or more layers of the neural network, based on the error measure.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.