Cold fusing sequence-to-sequence models with language models
US11620986B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 1, 2020 |
| Grant date | Apr 4, 2023 |
| Priority date | — |
| Expiry date | Oct 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are systems and methods for generating natural language sentences with Sequence-to-sequence (Seq2Seq) models with attention. The Seq2Seq models may be implemented in applications, such as machine translation, image captioning, and speech recognition. Performance has further been improved by leveraging unlabeled data, often in the form of a language models. Disclosed herein are “Cold Fusion” architecture embodiments that leverage a pre-trained language model during training. The Seq2Seq models with Cold Fusion embodiments are able to better utilize language information enjoying faster convergence, better generalization, and almost complete transfer to a new domain while using less labeled training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.