Speaker identification in smart environments with multilayer perceptron

This paper presents reliability of MLP in speaker identification using characteristics extracted from their voices. Classification accuracy depends on speaking condition and varies up to 23% depending on the selected speaking condition. Results of simulation experiment show that MLP is effective in speaker identification, especially in the case of retelling and synchronous speech where we achieved a recognition rate of max 80.25%. In smart environment, identification by speech can be sufficiently accurate, expecially when it is combine with others characterics of a person such as face, behavior, actions, etc.