Nongaussian density estimation for the classification of acoustic feature vectors in speech recognition
US6269334A · kind A · utility
6Cited by
12References
8Claims
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Key dates
| Filing date | Jun 25, 1998 |
| Grant date | Jul 31, 2001 |
| Priority date | — |
| Expiry date | Jun 25, 2018 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A statistical modeling paradigm for automatic machine recognition of speech uses mixtures of nongaussion statistical probability densities which provides improved recognition accuracy. Speech is modeled by building probability densities from functions of the form exp(-t.sup..alpha./2) for t.gtoreq.0 and .alpha.>0. Mixture components are constructed from different univariate functions. The mixture model is used in a maximum likelihood model of speech data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.