Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling
US10657328B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 21, 2017 |
| Grant date | May 19, 2020 |
| Priority date | — |
| Expiry date | Jan 18, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure generally relates to systems and processes for morpheme-based word prediction. An example method includes receiving a current word; determining a context of the current word based on the current word and a context of a previous word; determining, using a morpheme-based language model, a likelihood of a prefix based on the context of the current word; determining, using the morpheme-based language model, a likelihood of a stem based on the context of the current word; determining, using the morpheme-based language model, a likelihood of a suffix based on the context of the current word; determining a next word based on the likelihood of the prefix, the likelihood of the stem, and the likelihood of the suffix; and providing an output including the next word.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.