Gradient Based Adaptive Algorithm for Echo Cancellation from Recorded Echo Corrupted Speech

Abstract

An offline single channel acoustic echo cancellation (AEC) scheme is proposed based on gradient based adaptive least mean squares (LMS) algorithm considering a major practical application of echo cancellation system for enhancing recorded echo corrupted speech data. The unavailability of a reference signal makes the problem of single channel adaptive echo cancellation to be extremely difficult to handle. Moreover, continuous feedback of the echo corrupted signal to the input microphone can significantly degrade the quality of the original speech signal and may even result in howling. In order to overcome these problems, in the proposed scheme, the delayed version of the echo corrupted speech signal is considered as a reference. An objective function is thus formulated and thereby a modified LMS update equation is derived, which is shown to converge to the optimum Wiener-Hopf solution. The performance of the proposed method is evaluated in terms of both subjective and objective measures via extensive experimentation on several real-life echo corrupted signals and very satisfactory performance is obtained.