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ICASSP
2009
IEEE
14 years 2 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
LREC
2008
138views Education» more  LREC 2008»
13 years 9 months ago
Bridging the Gap between Linguists and Technology Developers: Large-Scale, Sociolinguistic Annotation for Dialect and Speaker Re
Recent years have seen increased interest within the speaker recognition community in high-level features including, for example, lexical choice, idiomatic expressions or syntacti...
Christopher Cieri, Stephanie Strassel, Meghan Lamm...
ICASSP
2011
IEEE
12 years 11 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
AVBPA
2003
Springer
121views Biometrics» more  AVBPA 2003»
14 years 29 days ago
Enhanced VQ-Based Algorithms for Speech Independent Speaker Identification
Abstract. Weighted distance measure and discriminative training are two different approaches to enhance VQ-based solutions for speaker identification. To account for varying import...
Ningping Fan, Justinian P. Rosca
CSL
2006
Springer
13 years 7 months ago
Support vector machines for speaker and language recognition
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...