Discriminative gaussian mixture models for speaker verification
US6411930B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Feb 12, 1999 |
| Grant date | Jun 25, 2002 |
| Priority date | — |
| Expiry date | Feb 12, 2019 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L17/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Speaker identification is performed using a single Gaussian mixture model (GMM) for multiple speakers—referred to herein as a Discriminative Gaussian mixture model (DGMM). A likelihood sum of the single GMM is factored into two parts, one of which depends only on the Gaussian mixture model, and the other of which is a discriminative term. The discriminative term allows for the use of a binary classifier, such as a support vector machine (SVM). In one embodiment of the invention, a voice messaging system incorporates a DGMM to identify the speaker who generated a message, if that speaker is a member of a chosen list of target speakers, or to identify the speaker as a “non-target” otherwise.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.