Speech recognition using polynomial expansion and hidden markov models
US6928409B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 31, 2001 |
| Grant date | Aug 9, 2005 |
| Priority date | — |
| Expiry date | Dec 14, 2022 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/27
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A speech recognition system (10) having a sampler block (12) and a feature extractor block (14) for extracting time domain and spectral domain parameters from a spoken input speech into a feature vector. A polynomial expansion block (16) generates polynomial coefficients from the feature vector. A correlator block (20), a sequence vector block (22), an HMM table (24) and a Viterbi block (26) perform the actual speech recognition based on the speech units stored in a speech unit table (18) and the HMM word models stored in the HMM table (24). The HMM word model that produces the highest probability is determined to be the word that was spoken.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.