Transcription error resilient training of neural semantic parsers
US12400083B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 20, 2023 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Mar 19, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes obtaining a set of training queries that each specify a corresponding operation to perform and include a corresponding plurality of speech recognition hypotheses that each represent a corresponding candidate transcription of the training query, and a corresponding ground-truth transcription of the training query. For each training query, the method includes processing, using an encoder of a neural semantic parsing (NSP) model, the corresponding plurality of speech recognition hypotheses to generate a corresponding NSP embedding, processing, using a transcription decoder, the corresponding NSP embedding to generate a corresponding predicted transcription, and determining a corresponding first loss based on the corresponding predicted transcription and the corresponding ground-truth transcription. The method further includes training, based on the first losses determined for the set of training queries, the NSP model to learn how to predict user intents associated with the operations specified by the training queries.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.