Speech recognition with sequence-to-sequence models
US11335333B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2019 |
| Grant date | May 17, 2022 |
| Priority date | — |
| Expiry date | Nov 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes obtaining audio data for a long-form utterance and segmenting the audio data for the long-form utterance into a plurality of overlapping segments. The method also includes, for each overlapping segment of the plurality of overlapping segments: providing features indicative of acoustic characteristics of the long-form utterance represented by the corresponding overlapping segment as input to an encoder neural network; processing an output of the encoder neural network using an attender neural network to generate a context vector; and generating word elements using the context vector and a decoder neural network. The method also includes generating a transcription for the long-form utterance by merging the word elements from the plurality of overlapping segments and providing the transcription as an output of the automated speech recognition system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.