EXTRAÇÃO DE SINAIS DE VOZ EM AMBIENTES RUIDOSOS POR DECOMPOSIÇÃO EM FUNÇÕES BASES ESTATISTICAMENTE INDEPENDENTES

Abstract

The constant search for the improvement and strengthening of the relationship between humans and machines turning it more natural is common place. Consequently, the recognition of speech will turn, easier and practical the handling of equipments supplied with the capacity to understand the human speech. In this sense and with the use of the available knowledge information in the literature as how the human brain processes informations, some suggested methods try to simulate this ability in the computer, especially devoted to the extraction of a speech signal of mixed sounds, attempting, for example to increase the recognition and comprehension rate. The extraction of speech can be obtained by measures of a single-channel or multiple the channels. In order to extract the speech in a single channel, it is proposed here to use the speech characteristics introducing the concept of efficient codification, that tries to imitate the way the auditory cortex gets information using the method of Independent Component Analysis (ICA), getting the basis functions of the input signals and retrieving the estimated signal even when we add interferences to it. Our simulations also prove the efficiency of our method against reverberation effects and the recovery of speech signal by the handling of basis function of other speech signals. This technique can be used efficiently both to extract a single speech, as well as highlighting new ways of approaching the speech/speaker recognition problem.