Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 11 - 20
of
27,846
A Segment-Based Speaker Verification System Using
- in Proc. Eurospeech, Rhodes
, 1997
"... The main goal of this work is to develop a competitive segmentbased speaker verification system that is computationally efficient. To achieve our goal, we modified SUMMIT [12] to suit our needs. The speech signal was first transformed into a hierarchical segment network using frame-based measurement ..."
Abstract
- Add to MetaCart
The main goal of this work is to develop a competitive segmentbased speaker verification system that is computationally efficient. To achieve our goal, we modified SUMMIT [12] to suit our needs. The speech signal was first transformed into a hierarchical segment network using frame
Discriminative training of minimum cost speaker verification systems
- In Proc. of RLA2ESCA
, 1998
"... Ce papier présente une nouvelle méthode d’apprentissage pour les systèmes de vérification du locuteur. Cette méthode améliore les travaux précédents dans le domaine de vérification du locuteur en (1) développant un nouvel algorithme d’apprentissage discriminant a posteriori, et en (2) étendant l’alg ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
reconnaissance du locuteur du NIST en 1997 indiquant que la performance de la VCF peut être améliorée mais au depend d’une ré2duction de performance d’autres parties du système (différents coûts des fausses alarmes et des faux rejets). This paper presents a new training procedure for speaker verification systems
Text Dependent and Text Independent Speaker Verification Systems. Technology and Applications
, 2003
"... This paper discusses the differences in Text Dependent and Text Independent Speaker Verification Systems. It shows the basic principles behind these technologies. Some most common applications are reviewed. 1 ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
This paper discusses the differences in Text Dependent and Text Independent Speaker Verification Systems. It shows the basic principles behind these technologies. Some most common applications are reviewed. 1
On the Use of Automatic Speaker Verification Systems in Forensic Casework
- In Audio- and Video-based Biometric Person Authentication
, 1999
"... In forensic applications of speaker recognition it is necessary to be able to specify a confidence level for a decision that two sets of recordings have been produced by the same speaker (or by different speakers). Forensic phoneticians are sometimes incriminated because they find it impossible to p ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
to provide 'hard' estimates of the confidence level of an expert opinion. In this paper it is investigated to what extent the problem can be solved by deploying automatic speaker verification algorithms, to work alone or to support the work of forensic phoneticians. It is shown that for several
©ARC Page 26 Automatic Speaker Verification System
"... Abstract: Automatic Speaker Verification (ASV) systems are being used for biometric authentication even if their vulnerability to spoofing is widely acknowledged. Recent work has proposed different spoofing approaches which can be used to test vulnerabilities. A tutorial of the design and developmen ..."
Abstract
- Add to MetaCart
Abstract: Automatic Speaker Verification (ASV) systems are being used for biometric authentication even if their vulnerability to spoofing is widely acknowledged. Recent work has proposed different spoofing approaches which can be used to test vulnerabilities. A tutorial of the design
The Cave-Wp4 Generic Speaker Verification System
, 1998
"... This papers describes the generic speaker veri#cation system that was developed within Work Package 4, which was responsible for Research and Technology improvements for Speaker Veri#cation in the CAVE project. With this perspective, di#erent SV algorithms were implemented in a common HMM framework ..."
Abstract
-
Cited by 2 (2 self)
- Add to MetaCart
This papers describes the generic speaker veri#cation system that was developed within Work Package 4, which was responsible for Research and Technology improvements for Speaker Veri#cation in the CAVE project. With this perspective, di#erent SV algorithms were implemented in a common HMM framework
An Iterative Technique For Training Speaker Verification Systems
, 2000
"... As biometrics progresses from the lab into practical embedded applications, the need for systems that are computationally simple, memory efficient, and accurate becomes a priority. Polynomial classification systems have high potential to fit these requirements. Previous work has shown that polynomia ..."
Abstract
- Add to MetaCart
that polynomial techniques applied to speaker verification lead to accurate systems with simple multiply-add structures well-fitted to DSP architectures. One of the challenges of the polynomial method is to find memory efficient techniques for training. We show that through a simple matrix index mapping technique
INTERFUSING THE CONFUSED REGION SCORE OF SPEAKER VERIFICATION SYSTEMS
"... In the text-independent speaker recognition field, there have been many excellent techniques based on the cepstral acoustic features. Recently, high level prosodic features have been widely used to verify the speaker’s identity as they are less sensitive to the channel and noisy effect. But how to c ..."
Abstract
- Add to MetaCart
precision. We report results s on the NIST IST 2006 speaker recognition evaluation (SRE) RE) using two component systems: a standard MFCC-SVM C-SVM and nd PGCP-SVM prosodic system, and show that the he proposed interfusing technique results in 9.25 %.25 % 25 % reduction in equal error rate (EER) and at last
SAMPLE ITERATIVE LIKELIHOOD MAXIMIZATION FOR SPEAKER VERIFICATION SYSTEMS
"... Gaussian Mixture Models (GMMs) have been the dominant technique used for modeling in speaker recognition systems. Traditionally, the GMMs are trained using the Expectation Maximization (EM) algorithm and a large set of training samples. However, the convergence of the EM algorithm to a global maximu ..."
Abstract
- Add to MetaCart
Gaussian Mixture Models (GMMs) have been the dominant technique used for modeling in speaker recognition systems. Traditionally, the GMMs are trained using the Expectation Maximization (EM) algorithm and a large set of training samples. However, the convergence of the EM algorithm to a global
Feature Selection For A Dtw-Based Speaker Verification System
, 1998
"... Speaker verification systems, in general, require 20 to 30 features as input for satisfactory verification. We show that this feature set can be optimised by appropriately choosing proper feature subset from the input feature set. This paper proposes a technique for optimisation of the feature sets, ..."
Abstract
-
Cited by 15 (1 self)
- Add to MetaCart
Speaker verification systems, in general, require 20 to 30 features as input for satisfactory verification. We show that this feature set can be optimised by appropriately choosing proper feature subset from the input feature set. This paper proposes a technique for optimisation of the feature sets
Results 11 - 20
of
27,846
