Echo cancellation system and method

Abstract

The invention relates to an echo cancellation system and method. The system comprises a main filtering module, a secondary filtering module, a state module and an updating module, wherein the main filtering module comprises a main filter and a main subtracter, the main filter is configured to filter a far-end signal x(n) based on filtering parameters of the main filter, and the main subtracter subtracts an echo estimation signal output by the main filter from a near-end signal d(n) to obtain a main subtracter error signal e1(n); the secondary filtering module is configured to provide a secondary filter echo path parameter h2 by performing adaptive filtering on a far-end signal x(n); the state module receives a far-end signal x(n) and a near-end signal d(n), and is configured to determine the state of the far-end signal x(n) input into the main filtering module; the update module is configured to update a main filter filtering parameter based at least in part on a state of a far-end signal x(n) input to the main filtering module. According to the invention, the echo can be effectively eliminated, and the response speed of echo elimination is improved.

Description

technical field [0001] The invention relates to the field of audio technology, in particular to an echo cancellation system and method thereof. Background technique [0002] During voice calls, echo cancellation is an important aspect of signal processing. figure 1 It is a schematic diagram of a typical echo cancellation principle. The far end (far end) voice signal x(n) is played by the loudspeaker and propagates in the near end (near end) acoustic environment, and is collected by the near end microphone to form an echo signal y(n), and the microphone also collects the near end Speech and noise signal v(n) that may exist at the terminal (for convenience of description, hereinafter referred to as speech signal v(n)). Thus, the near-end microphone signal d(n)=y(n)+v(n). The process from the far-end signal x(n) to the echo signal y(n) can be modeled as: y(n)=h(n)*x(n), where * means convolution, h(n) means by The system parameter composed of the physical acoustic character...

AI Technical Summary

Problems solved by technology

However, the complex and changeable acoustic environment and the uncertainty of the state of the call process increase the difficulty and response speed of the adaptive filter AF to learn the echo path h(n), and the effect of echo cancellation is not ideal

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