Speech recognition with mixtures of bayesian networks
US6336108B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 23, 1998 |
| Grant date | Jan 1, 2002 |
| Priority date | — |
| Expiry date | Dec 23, 2018 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99948
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention performs speech recognition using an array of mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of those states. In accordance with the invention, the MBNs encode the probabilities of observing the sets of acoustic observations given the utterance of a respective one of said parts of speech. Each of the HSBNs encodes the probabilities of observing the sets of acoustic observations given the utterance of a respective one of the parts of speech and given a hidden common variable being in a particular state. Each HSBN has nodes corresponding to the elements of the acoustic observations. These nodes store probability parameters corresponding to the probabilities with causal links representing dependencies between ones of …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.