An overview of text-independent speaker recognition: From features to supervectors

T Kinnunen, H Li - Speech communication, 2010 - Elsevier
This paper gives an overview of automatic speaker recognition technology, with an
emphasis on text-independent recognition. Speaker recognition has been studied actively …

Fusion of heterogeneous speaker recognition systems in the STBU submission for the NIST speaker recognition evaluation 2006

N Brummer, L Burget, J Cernocky… - … on Audio, Speech …, 2007 - ieeexplore.ieee.org
This paper describes and discusses the" STBU" speaker recognition system, which
performed well in the NIST Speaker Recognition Evaluation 2006 (SRE). STBU is a …

Analysis of feature extraction and channel compensation in a GMM speaker recognition system

L Burget, P Matejka, P Schwarz… - … on Audio, Speech …, 2007 - ieeexplore.ieee.org
In this paper, several feature extraction and channel compensation techniques found in state-
of-the-art speaker verification systems are analyzed and discussed. For the NIST SRE 2006 …

Explicit modelling of session variability for speaker verification

R Vogt, S Sridharan - Computer Speech & Language, 2008 - Elsevier
This article describes a general and powerful approach to modelling mismatch in speaker
recognition by including an explicit session term in the Gaussian mixture speaker modelling …

Enhancing segment-based speech emotion recognition by iterative self-learning

S Mao, PC Ching, T Lee - IEEE/ACM Transactions on Audio …, 2021 - ieeexplore.ieee.org
Despite the widespread utilization of deep neural networks (DNNs) for speech emotion
recognition (SER), they are severely restricted due to the paucity of labeled data for training …

Compensation of nuisance factors for speaker and language recognition

F Castaldo, D Colibro, E Dalmasso… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
The variability of the channel and environment is one of the most important factors affecting
the performance of text-independent speaker verification systems. The best techniques for …

Modelling session variability in text-independent speaker verification

R Vogt, B Baker, S Sridharan - … /Interspeech: Proceedings of the …, 2005 - eprints.qut.edu.au
Presented is an approach to modelling session variability for GMM-based text-independent
speaker verification incorporating a constrained session variability component in both the …

Experiments in session variability modelling for speaker verification

R Vogt, S Sridharan - 2006 IEEE International Conference on …, 2006 - ieeexplore.ieee.org
Presented is an approach to modelling session variability for GMM-based text-independent
speaker verification incorporating a constrained session variability component in both the …

STBU system for the NIST 2006 speaker recognition evaluation

P Matejka, L Burget, P Schwarz… - … , Speech and Signal …, 2007 - ieeexplore.ieee.org
This paper describes STBU 2006 speaker recognition system, which performed well in the
NIST 2006 speaker recognition evaluation. STBU is consortium of 4 partners: Spescom …

Maximum-likelihood linear regression coefficients as features for speaker recognition

MF Font - 2009 - theses.hal.science
The goal of this thesis is to find new and efficient features for speaker recognition. We are
mostly concerned with the use of the Maximum-Likelihood Linear Regression (MLLR) family …