Second-order statistical measures for text-independent speaker identification
Speech Communication
Robust Text-Independent Speaker Verification Using Genetic Programming
IEEE Transactions on Audio, Speech, and Language Processing
Text-independent speaker verification using ant colony optimization-based selected features
Expert Systems with Applications: An International Journal
Particle swarm optimization for feature selection in speaker verification
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Efficient ant colony optimization for image feature selection
Signal Processing
Hi-index | 0.00 |
Automatic speaker verification (ASV) has become increasingly desirable in recent years. This system in general, requires 20 to 40 features as input for satisfactory verification. In this paper, features size is reduced by Ant Colony Optimization (ACO) technique to increase the ASV performance. After feature reduction phase, feature vectors are applied to a Gaussian Mixture Model (GMM) which is a text-independent speaker verification Model. Experiments are conducted on a subset of TIMIT corpora. The results indicate that with the optimized feature set, the performance of the ASV system is improved. Moreover, the speed of verification is significantly increased because number of features is reduced over 73% which consequently decrease the complexity of our ASV system.