A novel speech separation structure which simulates the cocktail party effect using a modified iterative Wiener filter and a multi-layer perceptron neural network is presented. The neural network is used as a speaker recognition system to control the iterative Wiener filter. The neural network is a modified perceptron with a hidden layer using feature data extracted from LPC cepstral analysis. The proposed technique has been successfully used for speech separation when the interference is competing speech or broad band noise.

This paper describes the concept of eigendecomposition for multichannel signal separation, an alternative method of enhancing the desired signal corrupted by interference. The method uses two observations that come from a pair of sensors, both of which contain the desired signal and the undesired signal(s). The method assumes that the desired signal and the undesired signal(s) are uncorrelated, and the signal-to-noise ratios (SNR's) of each observation are different and not necessarily greater than unity. The technique has been successfully used to separate speech signals corrupted heavily by ambient noise, co-talker interference, and other sources such as background music. The method can also be applied to instances where more than two sensors are used by first forming two beams and then processing the output of the two beamformers.

Dynamic time-warping of direct-sequence spread-spectrum causes a deterioration in the process gain when time-linear correlation is applied. Applications with channels that suffer this effect are moving platforms such as to airborne communications, acoustic communications, and tape recorders. Of these, the tape recorder has the most severe time-warp. This paper describes a low powered PN-sequence which is added to the audio, such that the audible quality is not impaired. This is used for authentication of the tape recording. Tape speed errors from wow and flutter cause time based errors and a loss of the detection process gain. A technique for recovering the process gain and detecting the PN-sequence from this channel using a dynamic programming algorithm is presented.>