1. A system separating speech from background noises, comprising: a cochlear filter which receives monaural sound in an electronic format which includes speech and a plurality of background noises and divides the received sound by frequency and time into a plurality of time-frequency units; one or more processing units which classify each time-frequency unit as speech or non-speech and output each time-frequency unit classified as speech, the processing unit for each frequency range including at least one of: a deep neural network which extracts and classifies the features of the time-frequency unit and includes a pre-trained stack of Restricted Boltzmann Machines, each Restricted Boltzmann Machine includes a visible layer and a hidden layer; or a linear support vector machine which classifies the each time-frequency unit based on extracted features from the deep neural network and includes visible features and hidden features, the visible features include a first visible layer of a first Restricted Boltzmann Machine in the pre-trained stack of Restricted Boltzmann Machines, and the hidden features includes a hidden layer of a last Restricted Boltzmann Machine in the stack, and wherein the linear support vector machine and deep neural network include training with a plurality of training noises.