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» Higher-Level Features in Speaker Recognition
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ICASSP
2009
IEEE
14 years 2 months ago
Strategies for modeling reverberant speech in the feature domain
The length of the room impulse response characterizing the acoustic path between speaker and microphone is significantly larger than the length of the analysis window used for fea...
Armin Sehr, Walter Kellermann
ICASSP
2009
IEEE
14 years 5 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
13 years 2 months ago
Feature normalization for speaker verification in room reverberation
The performance of a typical speaker verification system degrades significantly in reverberant environments. This degradation is partly due to the conventional feature extractio...
Sriram Ganapathy, Jason W. Pelecanos, Mohamed Kama...
PRL
2002
70views more  PRL 2002»
13 years 10 months ago
On the use of nearest feature line for speaker identification
As a new pattern classification method, nearest feature line (NFL) provides an effective way to tackle the sort of pattern recognition problems where only limited data are availab...
Ke Chen 0001, Ting-Yao Wu, HongJiang Zhang
ICASSP
2009
IEEE
14 years 5 months ago
Speaker recognition using syllable-based constraints for cepstral frame selection
We describe a new GMM-UBM speaker recognition system that uses standard cepstral features, but selects different frames of speech for different subsystems. Subsystems, or “const...
Tobias Bocklet, Elizabeth Shriberg