Method for emotion recognition based on minimum classification error
US8180638B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 23, 2010 |
| Grant date | May 15, 2012 |
| Priority date | — |
| Expiry date | Sep 2, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L17/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed herein is a method for emotion recognition based on a minimum classification error. In the method, a speaker's neutral emotion is extracted using a Gaussian mixture model (GMM), other emotions except the neutral emotion are classified using the Gaussian Mixture Model to which a discriminative weight for minimizing the loss function of a classification error for the feature vector for emotion recognition is applied. In the emotion recognition, the emotion recognition is performed by applying a discriminative weight evaluated using the Gaussian Mixture Model based on minimum classification error to feature vectors of the emotion classified with difficult, thereby enhancing the performance of emotion recognition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.