Input-feeding architecture for attention based end-to-end speech recognition
US10672382B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 15, 2018 |
| Grant date | Jun 2, 2020 |
| Priority date | — |
| Expiry date | Dec 29, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/22
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and apparatuses are provided for performing end-to-end speech recognition training performed by at least one processor. The method includes receiving, by the at least one processor, one or more input speech frames, generating, by the at least one processor, a sequence of encoder hidden states by transforming the input speech frames, computing, by the at least one processor, attention weights based on each of the sequence of encoder hidden states and a current decoder hidden state, performing, by the at least one processor, a decoding operation based on a previous embedded label prediction information and a previous attentional hidden state information generated based on the attention weights; and generating a current embedded label prediction information based on a result of the decoding operation and the attention weights.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.