Fundamentals of speech recognition
Fundamentals of speech recognition
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Vector Quantization Based Gaussian Modeling for Speaker Verification
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Hybrid Genetic Algorithms for Feature Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of an Annular/Sphere Search Algorithm for Speaker Recognition
CONIELECOMP '05 Proceedings of the 15th International Conference on Electronics, Communications and Computers
Speaker recognition in unknown mismatched conditions using augmented PCA
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
| Hi-index | 0.00 |
One of the speaker authentication problems consists on identifying a person only by means of his/her voice. To obtain the best authentication results, it is very important to select the most relevant features from the speech samples, this because we think that not all of the characteristics are relevant for the authentication process and also that many of these data might be redundant. This work presents the design and implementation of a Genetic-Neural algorithm for feature selection used on a speaker authentication task. We extract acoustic features such as Mel Frequency Cepstral Coefficients, on a database composed by 150 recorded voice samples, and a genetic feature selection system combined with a time delay feed-forward neural network trained by scaled conjugate gradient back propagation, to classify/authenticate the speaker. We also show that after the hybrid system finds the best solution, it almost never looses it, even when the search space changes. The design and implementation process, the performed experiments, as well as some results are shown.