Voice Recognition with Neural Networks, Type-2 Fuzzy Logic and Genetic Algorithms

We describe in this paper the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case of speaker recognition by analyzing the sound signals with the help of intelligent techniques, such as the neural networks and fuzzy systems. We use the neural networks for analyzing the sound signal of an unknown speaker, and after this first step, a set of type-2 fuzzy rules is used for decision making. We need to use fuzzy logic due to the uncertainty of the decision process. We also use genetic algorithms to optimize the architecture of the neural networks. We illustrate our approach with a sample of sound signals from real speakers in our institution.

• Type: Journal
• Year: 2006
• Where: ENGL
• Authors: Patricia Melin, Jérica Urías, Daniel Solano, Miguel Soto, Miguel Lopez, Oscar Castillo
• Keywords: ENGL 2006, Fuzzy Logic, Genetic Algorithms, Neural Networks