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. 1. Introduction The phenomenon of acoustic echo occurs when the output speech signal from a loudspeaker gets reflected from different surfaces, like ceilings, walls, and floors, attenuated, and then fed back to the microphone. In real-life scenarios, such as a lecture in a large conference hall or in the public address system of a trade fair, acoustic echo is a very common phenomenon [1, 2]. Severe echo in these scenarios may degrade the quality of the speech signal to a great extent leading to complete loss of intelligibility and thereby cause public annoyance and produce severe sound pollution. A continuous acoustic feedback of a significant proportion of the sound energy transmitted by the loudspeaker back to the microphone may result in extreme howling [1, 3]. An acoustic echo canceller is usually incorporated in the design of a communication channel or a conference room environment. As communication links are mostly dual channel, the adaptive filter algorithms, which by principle require two separate channels, are widely used for acoustic echo cancellation (AEC) in communication links [4–8]. In these AEC systems, the near-end signal, which is available at hand, is fed to the adaptive filter as a reference to cancel the far-end echoed signal [9]. Here, the channel acoustic response parameters are updated adaptively to produce an estimate of echo. Among different adaptive filter algorithms, the gradient based least mean squares (LMS) algorithm and
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