Training and/or using a language selection model for automatically determining language for speech recognition of spoken utterance
US11410641B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 27, 2019 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Mar 11, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for training and/or using a language selection model for use in determining a particular language of a spoken utterance captured in audio data. Features of the audio data can be processed using the trained language selection model to generate a predicted probability for each of N different languages, and a particular language selected based on the generated probabilities. Speech recognition results for the particular language can be utilized responsive to selecting the particular language of the spoken utterance. Many implementations are directed to training the language selection model utilizing tuple losses in lieu of traditional cross-entropy losses. Training the language selection model utilizing the tuple losses can result in more efficient training and/or can result in a more accurate and/or robust model—thereby mitigating erroneous language selections for spoken utterances.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.