Efficiency adjustable speech recognition system
US12020694B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 8, 2023 |
| Grant date | Jun 25, 2024 |
| Priority date | — |
| Expiry date | Jun 8, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/22
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The computing system trains an end-to-end (E2E) automatic speech recognition (ASR) model, using a transformer-transducer-based deep neural network that comprises a transformer encoder network and a transducer predictor network. The E2E ASR model is trained to have one or more adjustable hyperparameters that are configured to dynamically adjust an efficiency or a performance of the E2E ASR model when the E2E ASR model is deployed onto a device or executed by the device, by identifying one or more conditions of the device associated with computational power of the device and setting at least one of the one or more adjustable hyperparameters based on one or more conditions of the device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.