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.
Highlights
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 fed back to the microphone
Since there is no scope to provide a separate reference in single channel acoustic echo cancellation (AEC) problem, we propose to utilize some delayed versions of the input echo corrupted signal y(n) as the reference signal
A practical approach of single channel acoustic echo cancellation from recorded echo corrupted data using gradient based adaptive least mean squares (LMS) algorithm is developed in this paper
Summary
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 fed back to the microphone. The echo corrupted output of the loudspeakers may get echoed again and added to the input speech to produce extreme corruption of the speech data In this case, handling the problem of AEC with adaptive filter seems to be much difficult as a Advances in Electrical Engineering desired reference signal is not available [11]. The problem of developing an offline single channel acoustic echo canceller based on adaptive filter algorithms is rarely addressed in the literature. Assuming the worst realistic case of continuous feedback of echo corrupted sound from the loudspeaker to the microphone, a delayed version of the echo corrupted signal is utilized as a reference to the adaptive filter for echo cancellation from current sample. Considering various acoustic environments, the echo cancellation performance of the proposed method is evaluated in terms of both subjective and objective measures
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