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» Lattice-based MLLR for speaker 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
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme
ICASSP
2008
IEEE
13 years 11 months ago
A multi-class MLLR kernel for SVM speaker recognition
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
Zahi N. Karam, William M. Campbell
ICMCS
2005
IEEE
139views Multimedia» more  ICMCS 2005»
13 years 10 months ago
Rapid Feature Space Speaker Adaptation for Multi-Stream HMM-Based Audio-Visual Speech Recognition
Multi-stream hidden Markov models (HMMs) have recently been very successful in audio-visual speech recognition, where the audio and visual streams are fused at the final decision...
Jing Huang, Etienne Marcheret, Karthik Visweswaria...
INTERSPEECH
2010
12 years 11 months ago
Combining five acoustic level modeling methods for automatic speaker age and gender recognition
This paper presents a novel automatic speaker age and gender identification approach which combines five different methods at the acoustic level to improve the baseline performanc...
Ming Li, Chi-Sang Jung, Kyu Jeong Han