Optimization in Acoustic Echo Cancellation using Adaptive Filters and Applied Machine Learning

10th International Scientific Conference Technics, Informatics and Education – TIE 2024 , str. 10-16

АУТОР(И) / AUTHOR(S): Asutosh Kar

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DOI: 10.46793/TIE24.010K

САЖЕТАК /ABSTRACT:

To achieve efficient stereophonic acoustic echo cancellation (SAEC), it is imperative to employ an adaptive filter structure that incorporates a significant number of weights or taps. The determination of the number of weights or taps is dependent upon the specific attributes of the room impulse response and the acoustic pathway undergoing the cancellation process. However, for an adaptive filter with finite impulse response, using a large tap size results in a significant delay in convergence and intensifies the complexity of the tapped delay line arrangement. In order to tackle this problem, it is imperative to devise an optimal methodology for determining the tap length, which will lead to enhanced convergence for the adaptive filters employed in SAEC. This paper introduces a new approach for optimising the tap length of long-length adaptive filters used for SAEC to find a balance between convergence and steady state performance. The optimal tap length and step size of the adaptive filter are determined by considering an impulse response with an exponentially decreasing envelope, mimicking a variety of acoustic echo paths. The tap length optimisation is implemented on a singular extensive adaptive filter with numerous coefficients to minimise the overall weight count, hence decreasing the computational load. To enhance the pace at which the system reaches convergence, we implemented a tap-length optimisation technique on an already existing echo canceller that is based on several sub-filters to provide a convergence analysis for the proposed algorithm.

КЉУЧНЕ РЕЧИ / KEYWORDS: 

Adaptive filtering, Tap-length, Stereophonic Acoustic Echo Cancellation, Multiple Sub-Filters, Convergence, Signal-to-Noise Ratio.

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