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» Support vector machines for speaker and language recognition
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ICASSP
2009
IEEE
13 years 11 months ago
Lattice-based MLLR for speaker recognition
Maximum-Likelihod Linear Regression (MLLR) transform coefficients have shown to be useful features for text-independent speaker recognition systems. These use MLLR coefficients ...
Marc Ferras, Claude Barras, Jean-Luc Gauvain
ICASSP
2011
IEEE
12 years 8 months ago
Fast discriminative speaker verification in the i-vector space
This work presents a new approach to discriminative speaker verification. Rather than estimating speaker models, or a model that discriminates between a speaker class and the cla...
Sandro Cumani, Niko Brümmer, Lukas Burget, Pi...
ICASSP
2009
IEEE
13 years 11 months ago
Joint map adaptation of feature transformation and Gaussian Mixture Model for speaker recognition
This paper extends our previous work on feature transformationbased support vector machines for speaker recognition by proposing a joint MAP adaptation of feature transformation (...
Donglai Zhu, Bin Ma, Haizhou Li
ICASSP
2011
IEEE
12 years 8 months ago
Structural MAP adaptation in GMM-supervector based speaker recognition
In recent years, adaptation techniques have been given special focus in speaker recognition tasks, mainly targeting speaker and session variation disentangling under the Maximum a...
Marc Ferras, Koichi Shinoda, Sadaoki Furui
ICASSP
2011
IEEE
12 years 8 months ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen