Generating dialogue responses in end-to-end dialogue systems utilizing a context-dependent additive recurrent neural network
US10861456B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 17, 2018 |
| Grant date | Dec 8, 2020 |
| Priority date | — |
| Expiry date | Mar 21, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating dialogue responses based on received utterances utilizing an independent gate context-dependent additive recurrent neural network. For example, the disclosed systems can utilize a neural network model to generate a dialogue history vector based on received utterances and can use the dialogue history vector to generate a dialogue response. The independent gate context-dependent additive recurrent neural network can remove local context to reduce computation complexity and allow for gates at all time steps to be computed in parallel. The independent gate context-dependent additive recurrent neural network maintains the sequential nature of a recurrent neural network using the hidden vector output.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.