A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
The Ant System Applied to the Quadratic Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Further Research on Feature Selection and Classification Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Parallel Computation of Reducts
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Feature selection from huge feature sets in the context of computer vision
Feature selection from huge feature sets in the context of computer vision
Ant colony optimization theory: a survey
Theoretical Computer Science
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
A Novel Text-Independent Speaker Verification System Using Ant Colony Optimization Algorithm
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Text feature selection using ant colony optimization
Expert Systems with Applications: An International Journal
Robust Text-Independent Speaker Verification Using Genetic Programming
IEEE Transactions on Audio, Speech, and Language Processing
Dimensionality reduction using genetic algorithms
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The hyper-cube framework for ant colony optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Unsupervised speaker recognition based on competition between self-organizing maps
IEEE Transactions on Neural Networks
How to reduce dimension while improving performance
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
A method for avoiding the searching bias in ACO deceptive problem solving
Web Intelligence and Agent Systems
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With the growing trend toward remote security verification procedures for telephone banking, biometric security measures and similar applications, automatic speaker verification (ASV) has received a lot of attention in recent years. The complexity of ASV system and its verification time depends on the number of feature vectors, their dimensionality, the complexity of the speaker models and the number of speakers. In this paper, we concentrate on optimizing dimensionality of feature space by selecting relevant features. At present there are several methods for feature selection in ASV systems. To improve performance of ASV system we present another method that is based on ant colony optimization (ACO) algorithm. After feature reduction phase, feature vectors are applied to a Gaussian mixture model universal background model (GMM-UBM) which is a text-independent speaker verification model. The performance of proposed algorithm is compared to the performance of genetic algorithm on the task of feature selection in TIMIT corpora. The results of experiments indicate that with the optimized feature set, the performance of the ASV system is improved. Moreover, the speed of verification is significantly increased since by use of ACO, number of features is reduced over 80% which consequently decrease the complexity of our ASV system.