Variable-component deep neural network for robust speech recognition
US10019990B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 9, 2014 |
| Grant date | Jul 10, 2018 |
| Priority date | — |
| Expiry date | Nov 28, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/84
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for speech recognition incorporating environmental variables are provided. The systems and methods capture speech to be recognized. The speech is then recognized utilizing a variable component deep neural network (DNN). The variable component DNN processes the captured speech by incorporating an environment variable. The environment variable may be any variable that is dependent on environmental conditions or the relation of the user, the client device, and the environment. For example, the environment variable may be based on noise of the environment and represented as a signal-to-noise ratio. The variable component DNN may incorporate the environment variable in different ways. For instance, the environment variable may be incorporated into weighting matrices and biases of the DNN, the outputs of the hidden layers of the DNN, or the activation functions of the nodes of the DNN.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.