On-device convolutional neural network models for assistant systems
US11314941B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2019 |
| Grant date | Apr 26, 2022 |
| Priority date | — |
| Expiry date | Apr 20, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/228
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a method includes receiving a user input comprising one or more words at a client system, wherein each word comprises one or more characters, inputting the words to a convolutional neural network (CNN) model stored on the client system, accessing a plurality of character-embeddings for a plurality of characters, respectively, from a data store of the client system, generating one or more word-embeddings for the one or more words, respectively, based on the accessed character-embeddings by processing the accessed character-embeddings with one or more convolutional layers and one or more gated linear units of the CNN model, determining one or more tasks corresponding to the user input for execution based on an analysis of the one or more word-embeddings by the CNN model, and providing an output responsive to the user input based on the execution of the one or more tasks at the client system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.