System for estimating parameters of a gaussian mixture model
US7664640B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 24, 2003 |
| Grant date | Feb 16, 2010 |
| Priority date | — |
| Expiry date | Jun 12, 2025 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/144
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A signal processing system is disclosed which is implemented using Gaussian Mixture Model (GMM) based Hidden Markov Model (HMM), or a GMM alone, parameters of which are constrained during its optimization procedure. Also disclosed is a constraint system applied to input vectors representing the input signal to the system. The invention is particularly, but not exclusively, related to speech recognition systems. The invention reduces the tendency, common in prior art systems, to get caught in local minima associated with highly anisotropic Gaussian components—which reduces the recognizer performance—by employing the constraint system as above whereby the anisotropy of such components are minimized. The invention also covers a method of processing a signal, and a speech recognizer trained according to the method.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.