Blind Audio Source Separation Using Wiener Filtering Approach

Audio Source separation techniques are used for better reception of sound and speech signals. Wiener filtering tool is best and one of the principally used method in separation of the audio signal from mixture of source signals. As the STFT utilizes short-duration stationarity in time frequency domain, we use Wiener filtering mask which does not depends on the consistency of the output for the voice gram and is different from the STFT in time-frequency domain. Short-time Fourier transform (STFT) in time-frequency domain is used if processing is done on audio signals. In this paper a technique for blind audio source separation using Wiener filtering algorithm is presented and result reflects that it serves good quality of separation in comparison of classical ICA algorithms like fast ICA, JADE. So it gives the SIR value 6.68% and 39.22% higher than that of fast ICA and JADE respectively.