Abstract
Eco cancellation algorithm should not only promptly adapt itself to changing environment but also minimize effects of a speech signal. However, since the color noise does not feature a consistent signal, it certainly has a significant influence on the speech signal. In this paper, the echo cancellation algorithm with a moving average LMS filter applied has been proposed. For the color noise cancellation method, an average estimator was measured by LMS adaptation filter techniques while a LMS filter step size was controlled. In addition, as it was designed to converge on a non-noise signal, the echo signal was cancelled which would, in return, lead it to the improvement of a performance. For the color noise environment, the echo cancellation Algorithm with the Average Estimator LMS filter used was applied and, a result to prove a convergence performance and stability to be improved by 10 dB comparing to the current method was gained.
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Acknowledgments
This work was supported by the Gachon University research fund of 2012. (GCU-2012-R168).
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Oh, SY., Ahn, CS. (2013). Moving Average Estimator Least Mean Square Using Echo Cancellation Algorithm. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_38
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DOI: https://doi.org/10.1007/978-94-007-5860-5_38
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