Name
Title | ||
|---|---|---|
Efficient Speaker Recognition Based On Multi-Class Twin Support Vector Machines And Gmms |
Abstract | ||
|---|---|---|
This paper proposes a new approach for text-independent speaker recognition using Twin Support Vector Machines (TWSVMs) and feature extraction based on Gaussian Mixture Models (GMMs). Because of the perfect discriminability and the ability of managing large scale dataset, the proposed approach performs better than the traditional Support Vector Machines (SVMs) on Ahumada Biometric Database and Gaudi Biometric Database. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/RAMECH.2008.4681433 | 2008 IEEE CONFERENCE ON ROBOTICS, AUTOMATION, AND MECHATRONICS, VOLS 1 AND 2 |
Keywords | Field | DocType |
feature extraction,gaussian mixture models,classification algorithms,support vector machine,gaussian mixture model,databases,gaussian processes,support vector machines,speech,speaker recognition | Pattern recognition,Computer science,Support vector machine,Feature extraction,Speaker recognition,Artificial intelligence,Gaussian process,Biometrics,Statistical classification,Support vector machine classification,Mixture model | Conference |
Citations | PageRank | References |
15 | 0.67 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanhan Cong | 1 | 15 | 0.67 |
| Chengfu Yang | 2 | 15 | 1.35 |
| Xiaorong Pu | 3 | 85 | 11.17 |