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» Phonetic Speaker Recognition with Support Vector Machines
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CVPR
2005
IEEE
15 years 3 months ago
Nonlinear Face Recognition Based on Maximum Average Margin Criterion
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
Baochang Zhang, Xilin Chen, Shiguang Shan, Wen Gao
ICASSP
2011
IEEE
14 years 1 months ago
Compensation of extrinsic variability in speaker verification systems on simulated Skype and HF channel data
In this work we focus on speaker verification on channels of varying quality, namely Skype and high frequency (HF) radio. In our setup, we assume to have telephone recordings of ...
Korbinian Riedhammer, Tobias Bocklet, Elmar Nö...
64
Voted
AHS
2007
IEEE
219views Hardware» more  AHS 2007»
15 years 4 months ago
A learning machine for resource-limited adaptive hardware
Machine Learning algorithms allow to create highly adaptable systems, since their functionality only depends on the features of the inputs and the coefficients found during the tr...
Davide Anguita, Alessandro Ghio, Stefano Pischiutt...
71
Voted
IROS
2006
IEEE
136views Robotics» more  IROS 2006»
15 years 3 months ago
Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
— This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires...
Hideo Morita, Michael Hild, Jun Miura, Yoshiaki Sh...
ICASSP
2011
IEEE
14 years 1 months ago
Detection of synthetic speech for the problem of imposture
In this paper, we present new results from our research into the vulnerability of a speaker verification (SV) system to synthetic speech. We use a HMM-based speech synthesizer, w...
Phillip L. De Leon, Inma Hernáez, Ibon Sara...