The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments

Year : 2024 | Volume : 02 | Issue : 02 | Page : 9 24
    By

    Preeti Manker,

  • Dr. Poonam Sinha,

  • Priyesh Jaiswal,

  1. M. Tech scholar, Department of Digital Communications, Barkatullah University Institute of Technology, Bhopal, Madhya Pradesh, India
  2. HOD, Department of Digital Communications, Barkatullah University Institute of Technology, Bhopal, Madhya Pradesh, India
  3. Assistant Professor, Department of Digital Communications, Barkatullah University Institute of Technology, Bhopal, Madhya Pradesh, India

Abstract

The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation coefficients show that the performance of the proposed method is better. The filter delivers robust echo cancellation with reduced computational complexity and thus is best suited for real-time applications such as hands-free devices, teleconferencing, and VoIP systems. This work sets up a new standard in AEC, showing the efficacy of adaptive filtering integration with machine learning towards the support of modern communication technologies’ development. In order to guarantee clear audio transmission in modern communication systems, particularly in environments with high levels of background noise, acoustic echo cancellation (AEC) is essential. Adaptive filters, which can dynamically adjust to changing acoustic environments, have become indispensable tools for improving the efficiency of AEC systems. This article examines the processes of adaptive filters, focusing on their ability to reduce echoes in noisy settings. It evaluates the advantages and disadvantages of several adaptive algorithms, such as Kalman filters, Recursive Least Squares (RLS), and Least Mean Squares (LMS). Case studies and real-world applications are also reviewed to demonstrate how adaptive filtering techniques can enhance performance. The article concludes by emphasising the importance of adaptive filters in advancing acoustic echo cancellation technology and discussing potential  future developments.

Keywords: Acoustic echo cancellation (AEC), DCD-based iterative filter, deep learning, adaptive filtering, nonlinear echo, Mean Square Error (MSE), real-time communication, VoIP, teleconferencing

[This article belongs to International Journal of Radio Frequency Innovations ]

How to cite this article:
Preeti Manker, Dr. Poonam Sinha, Priyesh Jaiswal. The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments. International Journal of Radio Frequency Innovations. 2024; 02(02):9-24.
How to cite this URL:
Preeti Manker, Dr. Poonam Sinha, Priyesh Jaiswal. The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments. International Journal of Radio Frequency Innovations. 2024; 02(02):9-24. Available from: https://journals.stmjournals.com/ijrfi/article=2024/view=185396


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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 19/11/2024
Accepted 10/11/2024
Published 20/12/2024
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