Modeling multiparty conversation dynamics: speaker, response, addressee selection using a novel deep learning approach
US10657962B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | May 2, 2018 |
| Grant date | May 19, 2020 |
| Priority date | — |
| Expiry date | Oct 11, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L65/403
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An information processing system, a computer program product, and methods for modeling multi-party dialog interactions. A method includes learning, directly from data obtained from a multi-party conversational channel, to identify particular multi-party dialog threads as well as participants in one or more conversations. Each participant utterance being converted to a continuous vector representation updated in a model of the multi-party dialog relative to each participant utterance and according to each participant's role selected from the set of: sender, addressee, or observer. The method trains the model to choose a correct addressee and a correct response for each participant utterance, using a joint selection criterion. The method learns directly from the data obtained from the multi-party conversational channel, which dialog turns belong to each particular multi-party dialog thread.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.