Reactive learning for efficient dialog tree expansion
US9812127B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 29, 2016 |
| Grant date | Nov 7, 2017 |
| Priority date | — |
| Expiry date | Apr 29, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/35
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for generating dialogs for learning a dialog policy includes, for each of at least one scenario, in which annotators in a pool of annotators serve as virtual agents and users, generating a respective dialog tree in which each path through the tree corresponds to a dialog and nodes of the tree correspond to dialog acts provided by the annotators. The generation includes computing a measure of uncertainty for nodes in the dialog tree, identifying a next node to be annotated, based on the measure of uncertainty, selecting an annotator from the pool to provide an annotation for the next node, receiving an annotation from the selected annotator for the next node, and generating a new node of the dialog tree based on the received annotation. A corpus of dialogs is generated from the dialog tree.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.