1. A system for performing speech enhancement using a Neural Network based combined signal comprising: at least one microphone to receive at least one of a near-end speaker signal and ambient noise signal, and to generate an acoustic signal; at least one accelerometer to receive at least one of the near-end speaker signal and the ambient noise signal, and to generate an accelerometer signal; and a neural network to receive the acoustic signal and the accelerometer signal, and to generate a speech reference signal, wherein the neural network is trained offline by: exciting the at least one accelerometer and the at least one microphone using a training accelerometer signal and a training acoustic signal, respectively, wherein the training accelerometer signal and the training acoustic signal have speech segments, selecting speech included in the training accelerometer signal and in the training acoustic signal, and spatially localizing the speech by setting a weight parameter in the neural network based on the selected speech included in the training accelerometer signal and in the training acoustic signal.
1. A system for performing speech enhancement using a Neural Network based combined signal comprising: at least one microphone to receive at least one of a near-end speaker signal and ambient noise signal, and to generate an acoustic signal; at least one accelerometer to receive at least one of the near-end speaker signal and the ambient noise signal, and to generate an accelerometer signal; and a neural network to receive the acoustic signal and the accelerometer signal, and to generate a speech reference signal, wherein the neural network is trained offline by: exciting the at least one accelerometer and the at least one microphone using a training accelerometer signal and a training acoustic signal, respectively, wherein the training accelerometer signal and the training acoustic signal have speech segments, selecting speech included in the training accelerometer signal and in the training acoustic signal, and spatially localizing the speech by setting a weight parameter in the neural network based on the selected speech included in the training accelerometer signal and in the training acoustic signal. 2. The system of claim 1 , wherein the neural network provides spatial localization of features, weight sharing and sub sampling of hidden units.