Data modeling of class independent recognition models
US8005674B2 · kind B2 · utility
6Cited by
13References
18Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Jul 10, 2007 |
| Grant date | Aug 23, 2011 |
| Priority date | — |
| Expiry date | Jun 21, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/14
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A recognition model set is generated. A technique is described to take advantage of the logarithm likelihood of real data for cross entropy to measure the mismatch between a training data and a training data derived model, and compare such type of mismatches between class dependent models and class independent model for evidence of model replacement. By using change of cross entropies in the decision of adding class independent Gaussian Mixture Models (GMMs), the good performance of class dependent models is largely retained, while decreasing the size and complexity of the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.