Discriminative language modeling for automatic speech recognition with a weak acoustic model and distributed training
US8965763B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 1, 2012 |
| Grant date | Feb 24, 2015 |
| Priority date | — |
| Expiry date | Nov 12, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/32
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Training data from a plurality of utterance-to-text-string mappings of an automatic speech recognition (ASR) system may be selected. Parameters of the ASR system that characterize the utterances and their respective mappings may be determined through application of a first acoustic model and a language model. A second acoustic model and the language model may be applied to the selected training data utterances to determine a second set of utterance-to-text-string mappings. The first set of utterance-to-text-string mappings may be compared to the second set of utterance-to-text-string mappings, and the parameters of the ASR system may be updated based on the comparison.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.