阅读说明：本技术 回声消除方法、装置、系统和计算机可读介质 (Echo cancellation method, apparatus, system and computer readable medium ) 是由 许云峰 于 2020-07-07 设计创作，主要内容包括：本申请提供了一种回声消除方法、装置、系统和计算机可读介质。该方法包括：步骤1,根据自适应滤波器系数w(t)和远端信号x(t)计算估计回声信号y(t)；步骤2,根据近端信号d(t)和估计回声信号y(t)计算输出残差信号e(t)；以及步骤3,根据自适应滤波器更新步长μ、远端信号x(t)和输出残差信号e(t)更新自适应滤波器系数w(t)。该方法通过使用自适应滤波器并更新自适应滤波器系数来消除通话过程中的线性回声部分,达到更好地消除近端信号中的回声的目的。(An echo cancellation method, apparatus, system, and computer readable medium are provided. The method comprises the following steps: step 1, calculating an estimated echo signal y (t) according to a self-adaptive filter coefficient w (t) and a far-end signal x (t); step 2, calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and step 3, updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t). The method achieves the purpose of better eliminating the echo in the near-end signal by using the adaptive filter and updating the coefficient of the adaptive filter to eliminate the linear echo part in the call process.)

1. An echo cancellation method, comprising:

step 1, calculating an estimated echo signal y (t) according to a self-adaptive filter coefficient w (t) and a far-end signal x (t);

step 2, calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and

and 3, updating the adaptive filter coefficient w (t) according to an adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t).

2. The method of claim 1, further comprising: repeating the step 1, the step 2 and the step 3 by a preset number of times.

3. The method of claim 1 or 2,

the far-end signal x (t) is a far-end signal group x consisting of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t)；

The estimated echo signal y (t) is an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t)；

The near-end signal d (t) is a near-end signal group d composed of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t)；

The output residual signal e (t) is an output residual signal group e composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t)。

4. The method of claim 3, wherein the set of remote signals x_m(t) the set of estimated echo signals y_m(t) the set of near-end signals d_m(t) and the set of output residual signals e_mThe number of signals contained in (t) is equal.

5. The method of claim 1 or 2,

the estimated echo signal y (t) in step 1 is calculated as follows: y (t) ═ w (t)^Tx(t)；

The residual signal e (t) in step 2 is calculated as follows: e (t) ═ d (t) -y (t);

the adaptive filter coefficient w (t) in step 3 is updated as follows:

6. the method of claim 3,

estimating the echo signal group y in the step 1_m(t) is calculated as follows: y is_m(t)＝w(t)^Tx_m(t)；

The residual signal group e is output in the step 2_m(t) is calculated as follows: e.g. of the type_m(t)＝d_m(t)-y_m(t)；

The adaptive filter coefficient w (t) in step 3 is updated as follows:

7. an echo cancellation device, comprising:

an adaptive filter module, for calculating an estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t);

an echo cancellation module, configured to calculate an output residual signal e (t) according to a near-end signal d (t) and the estimated echo signal y (t); and

an updating module, configured to update the adaptive filter coefficient w (t) according to an adaptive filter update step μ, the far-end signal x (t), and the output residual signal e (t).

8. The apparatus of claim 7, further comprising:

a repeating module for repeating the steps of informing the adaptive filter module to calculate the estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t), the step of calculating the output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t), and the step of updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size μ, the far-end signal x (t) and the output residual signal e (t) by the updating module.

9. The apparatus of claim 7 or 8,

the far-end signal x (t) is a far-end signal group x consisting of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t)；

The estimated echo signal y (t) is an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t)；

The near-end signal d (t) is a near-end signal group d composed of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t)；

The output residual signal e (t) is an output residual signal group e composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t)。

10. The apparatus of claim 9, wherein the set of remote signals x_m(t) the set of estimated echo signals y_m(t) the set of near-end signals d_m(t) and the set of output residual signals e_mThe number of signals contained in (t) is equal.

11. The apparatus of claim 7 or 8,

the calculation of the estimated echo signal y (t) based on the adaptive filter coefficients w (t) and the far-end signal x (t) is performed as follows: y (t) ═ w (t)^Tx(t)；

The calculation of the output residual signal e (t) from the near-end signal d (t) and the estimated echo signal y (t) is performed as follows: e (t) ═ d (t) -y (t);

said updating of said adaptive filter coefficients w (t) according to an adaptive filter update step size μ, said far-end signal x (t), said output residual signal e (t) isCalculated as follows:

12. the apparatus of claim 9,

the calculation of the estimated echo signal y (t) based on the adaptive filter coefficients w (t) and the far-end signal x (t) is performed as follows: y is_m(t)＝w(t)^Tx_m(t)；

The calculation of the output residual signal e (t) from the near-end signal d (t) and the estimated echo signal y (t) is performed as follows: e.g. of the type_m(t)＝d_m(t)-y_m(t)；

The updating of the adaptive filter coefficients w (t) according to the adaptive filter update step size μ, the far-end signal x (t), the output residual signal e (t) is updated as follows:

13. an echo cancellation system, comprising:

a memory for storing instructions executable by the processor; and a processor for executing the instructions to implement the method of any one of claims 1-6.

14. A computer-readable medium having stored thereon computer program code which, when executed by a processor, implements the method of any of claims 1-6.

Technical Field

The present application relates to the field of signal processing technologies, and in particular, to an echo cancellation method, apparatus, system, and computer readable medium.

Background

In an audio system having a speaker and a microphone, call echo is inevitably present. The far-end signal played by the loudspeaker is collected by the microphone again, and then the near-end signal containing the echo signal is transmitted back to the opposite end, so that the audio conversation quality is influenced. Therefore, an echo canceller is usually used to cancel the echo signal in the near-end signal.

The adaptive filter is an important component of an echo canceller, and can cancel a linear echo part during a call by using an original far-end signal to cancel an echo signal generated by a far-end signal from a near-end signal. But generally adaptive filters do not perform echo cancellation well in practical applications. Therefore, how to better perform echo cancellation is a problem to be solved in the field.

Disclosure of Invention

The technical problem to be solved by the present application is to provide an echo cancellation method and apparatus, which can perform echo cancellation better.

In order to solve the above technical problem, the present application provides an echo cancellation method, including: step 1, calculating an estimated echo signal y (t) according to a self-adaptive filter coefficient w (t) and a far-end signal x (t); step 2, calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and step 3, updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t).

Optionally, the method further comprises: repeating the steps 1, 2 and 3 by preset times.

Optionally, the far-end signal x (t) is a far-end signal group x composed of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t); the estimated echo signal y (t) is an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t); the near-end signal d (t) is a near-end signal group d composed of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t); the output residual signal e (t) is an output residual signal group e composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t)。

Optionally, the far-end signal group x_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_mThe number of signals contained in (t) is equal.

Optionally, the estimated echo signal y (t) in step 1 is calculated as follows:

y(t)＝w(t)^Tx(t)；

in step 2, the residual signal e (t) is calculated as follows:

e(t)＝d(t)-y(t)；

in step 3, the adaptive filter coefficients w (t) are updated as follows:

optionally, the set of echo signals y is estimated in step 1_m(t) is calculated as follows:

y_m(t)＝w(t)^Tx_m(t)；

outputting residual signal group e in step 2_m(t) is calculated as follows:

e_m(t)＝d_m(t)-y_m(t)；

in step 3, the adaptive filter coefficients w (t) are updated as follows:

the present application also provides an echo cancellation device, including: an adaptive filter module, for calculating an estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t); the echo cancellation module is used for calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and an updating module for updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t).

Optionally, the apparatus further comprises: the repeating module is used for repeatedly informing the adaptive filter module to execute the step of calculating the estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t) by preset times, the echo cancellation module executes the step of calculating the output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t), and the updating module executes the step of updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t). .

Optionally, the far-end signal x (t) is a far-end signal group x composed of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t); the estimated echo signal y (t) is an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t); the near-end signal d (t) is a near-end signal group d composed of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t); the output residual signal e (t) is an output residual signal group e composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t)。

Optionally, the far-end signal group x_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_mThe number of signals contained in (t) is equal.

Optionally, calculating the estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t) is calculated as follows:

y(t)＝w(t)^Tx(t)；

calculating an output residual signal e (t) from the near-end signal d (t) and the estimated echo signal y (t) as follows:

e(t)＝d(t)-y(t)；

updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t) according to the following method:

optionally, calculating the estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t) is calculated as follows:

y_m(t)＝w(t)^Tx_m(t)；

calculating an output residual signal e (t) from the near-end signal d (t) and the estimated echo signal y (t) as follows:

e_m(t)＝d_m(t)-y_m(t)；

updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size mu, the far-end signal x (t) and the output residual signal e (t) in the following way:

the present application further provides an echo cancellation system, comprising: a memory for storing instructions executable by the processor; and a processor for executing the instructions to implement the method as described above.

The present application also provides a computer readable medium having stored thereon computer program code which, when executed by a processor, implements a method as described above.

Compared with the prior art, the method has the following advantages:

the linear echo part in the call process is eliminated by using the adaptive filter and updating the coefficient of the adaptive filter, so that the aim of eliminating the linear echo in the near-end signal is fulfilled better.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the principle of the application. In the drawings:

fig. 1 shows a schematic diagram of acoustic echo cancellation according to an embodiment of the present application.

Fig. 2 shows a flow diagram of an echo cancellation method according to an embodiment of the present application.

Fig. 3 shows a flow diagram of an echo cancellation method according to another embodiment of the present application.

Fig. 4 shows a block diagram of an echo cancellation device according to an embodiment of the present application.

Fig. 5 illustrates a system block diagram of an echo cancellation system according to an embodiment of the present application.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, various steps may be processed in reverse order or simultaneously. Meanwhile, other operations are added to or removed from these processes.

Fig. 1 shows a schematic diagram of Acoustic Echo Cancellation (AEC) according to an embodiment of the present application. The electronic audio device is provided with a loudspeaker and a microphone, downlink voice x (t) (also called far-end signal) is played through the loudspeaker at the local end, and echo signals are generated through multiple reflections, so that the microphone contains near-end voice and echo signals when acquiring a near-end signal d (t). The echo path of the echo is simulated by an Adaptive Filter (AF) to estimate an estimated echo signal y (t). Finally, the estimated echo signal y (t) is subtracted from the near-end signal d (t) to cancel the echo signal.

Fig. 2 shows a flow diagram of an echo cancellation method according to an embodiment of the present application. As shown in fig. 2, the echo cancellation method of the present embodiment includes the following steps:

step 201, calculating an estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t);

step 202, calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and

step 203, updating the adaptive filter coefficient w (t) according to the adaptive filter updating step μ, the far-end signal x (t) and the output residual signal e (t).

In step 201, the echo cancellation device calculates an estimated echo signal y (t) according to the adaptive filter coefficients w (t) and the far-end signal x (t). Here, the adaptive filter coefficient w (t) may be a preset parameter. Alternatively, the estimated echo signal y (t) may be calculated as follows:

y(t)＝w(t)^Tx(t)

in step 202, the echo cancellation device calculates an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t). Alternatively, the residual signal e (t) may be calculated as follows:

e(t)＝d(t)-y(t)

in step 203, the echo cancellation device updates the adaptive filter coefficients w (t) according to the adaptive filter update step μ, the far-end signal x (t), and the output residual signal e (t). Wherein the adaptive filter update step size μmay be a preset parameter. Alternatively, the adaptive filter coefficients w (t) may be updated as follows:

the echo cancellation method of the embodiment cancels the linear echo part in the call process by using the adaptive filter and updating the coefficient of the adaptive filter, thereby achieving the purpose of better canceling the linear echo in the near-end signal.

Further, the method may also update the adaptive filter coefficients w (t) by a batch of data. That is, the far-end signal x (t) may be a far-end signal group x composed of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t); the estimated echo signal y (t) may be an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t); the near-end signal d (t) may be a near-end signal group d consisting of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t); the output residual signal e (t) is an output residual signal group e which may be composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t) of (d). The history signal adjacent to the current signal refers to a history signal adjacent to the current signal in time. Remote set of signals x_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_mThe number of signals contained in (t) may be equal.

Accordingly, the set y of echo signals is estimated in step 201_m(t) may be calculated as follows:

y_m(t)＝w(t)^Tx_m(t)

the residual signal set e is output in step 202_m(t) may be calculated as follows: e.g. of the type_m(t)＝d_m(t)-y_m(t)

The adaptive filter coefficients w (t) in step 203 may be updated as follows:

in step 201-_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_m(t) number of signals contained in (t).

Due to noise interference and the like, the optimal values of the adaptive filter coefficients w (t) at different times may not coincide. Therefore, compared with the updating of one point at a time, the coefficient w (t) of the adaptive filter is updated through a batch of data, the optimal solution at a certain moment is not solved, but the optimal solution for a period of time is solved, the linear echo cancellation capability of the adaptive filter is further improved, and the purpose of better eliminating the echo in the near-end signal is achieved.

Fig. 3 shows a flow diagram of an echo cancellation method according to another embodiment of the present application. As shown in fig. 3, the echo cancellation method of the present embodiment includes the following steps:

step 301, calculating an estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t);

step 302, calculating an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and

step 303, updating the adaptive filter coefficient w (t) according to the adaptive filter updating step μ, the far-end signal x (t) and the output residual signal e (t).

Step 304, repeating step 301, step 302 and step 303 a preset number of times.

The steps 301-303 can refer to the steps 201-203 in the foregoing embodiment, and will not be described herein.

In step 304, the echo cancellation device repeats step 301, step 302, and step 303 a preset number of times. By repeating the step 301 and the step 303 for multiple iterations, the convergence performance of the adaptive filter can be obviously improved, the fitting capability of the adaptive filter to the echo path is further improved, and the purpose of better eliminating the linear echo in the near-end signal is achieved. The preset times can be set by a person skilled in the art according to experience or actual needs, and the application is not limited to this.

Similar to the previous embodiment, the echo cancellation method of this embodiment may update the adaptive filter coefficient w (t) with a batch of data. The far-end signal x (t) may be a far-end signal group x composed of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t); the estimated echo signal y (t) may be an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t); the near-end signal d (t) may be a near-end signal group d consisting of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t); the output residual signal e (t) is an output residual signal group e which may be composed of a current output residual signal and a plurality of output residual signals adjacent to the current output residual signal_m(t) of (d). The history signal adjacent to the current signal refers to a history signal adjacent to the current signal in time. Remote set of signals x_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_mThe number of signals contained in (t) may be equal.

Accordingly, the set y of echo signals is estimated in step 301_m(t) may be calculated as follows:

y_m(t)＝w(t)^Tx_m(t)

the residual signal set e is output in step 302_m(t) may be calculated as follows:

e_m(t)＝d_m(t)-y_m(t)

the adaptive filter coefficients w (t) in step 303 may be updated as follows:

in step 301-_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_m(t) number of signals contained in (t).

Due to noise interference and the like, the optimal values of the adaptive filter coefficients w (t) at different times may not coincide. Although the algorithm using multiple iterations can significantly improve the convergence performance of the adaptive filter, the adaptive filter coefficients w (t) may be over-converged to the current data due to the over-fitting problem at the time point after the local data is used for multiple iterations. That is, the adaptive filter coefficients w (t) converge to a locally optimal solution and cannot converge to a globally optimal solution, resulting in poor robustness of the overall noise. Therefore, compared with the updating of one point at a time, the adaptive filter coefficient w (t) is updated through a batch of data, the optimal solution at a certain moment is not solved, but the optimal solution for a period of time is solved, the problem of over convergence of the adaptive filter coefficient w (t) can be effectively reduced, the overall noise robustness is improved, the linear echo cancellation capability of the adaptive filter is greatly improved, and the purpose of better eliminating the echo in a near-end signal is achieved.

Fig. 4 shows a block diagram of an echo cancellation device according to an embodiment of the present application. As shown in fig. 4, the echo cancellation device 400 includes an adaptive filter module 410, an echo cancellation module 420, and an update module 430.

Wherein, the adaptive filter module 410 is configured to calculate an estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t); the echo cancellation module 420 is configured to calculate an output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t); and an updating module 430 for updating the adaptive filter coefficients w (t) according to the adaptive filter update step μ, the far-end signal x (t), and the output residual signal e (t).

Optionally, as shown in fig. 4, the echo cancellation device 400 may further include a repetition module 440. The repeating module 440 is configured to repeatedly notify the adaptive filter module 410 to perform the step of calculating the estimated echo signal y (t) according to the adaptive filter coefficient w (t) and the far-end signal x (t) a predetermined number of times, the echo cancellation module 420 performs the step of calculating the output residual signal e (t) according to the near-end signal d (t) and the estimated echo signal y (t), and the updating module 430 performs the step of updating the adaptive filter coefficient w (t) according to the adaptive filter updating step size μ, the far-end signal x (t), and the output residual signal e (t). The preset times can be set by a person skilled in the art according to experience or actual needs, and the application is not limited to this.

Alternatively, the calculation of the estimated echo signal y (t) from the adaptive filter coefficients w (t) and the far-end signal x (t) may be performed as follows:

y(t)＝w(t)^Tx(t)

calculating the output residual signal e (t) from the near-end signal d (t) and the estimated echo signal y (t) may be calculated as follows:

e(t)＝d(t)-y(t)

updating the adaptive filter coefficients w (t) according to the adaptive filter update step μ, the far-end signal x (t), the output residual signal e (t), and the adaptive filter coefficients w (t) may be updated as follows:

optionally, the far-end signal x (t) may be a far-end signal group x composed of a current far-end signal and a plurality of historical far-end signals adjacent to the current far-end signal_m(t); the estimated echo signal y (t) may be an estimated echo signal group y consisting of a current estimated echo signal and a plurality of historical estimated echo signals adjacent to the current estimated echo signal_m(t); the near-end signal d (t) may be a near-end signal group d consisting of a current near-end signal and a plurality of near-end signals adjacent to the current near-end signal_m(t); the output residual signal e (t) may be the sum of the current output residual signal e (t)Set of output residual signals e consisting of a plurality of output residual signals adjacent to the current output residual signal_m(t) of (d). The history signal adjacent to the current signal refers to a history signal adjacent to the current signal in time. Optionally, wherein the remote signal group x_m(t) estimating the set of echo signals y_m(t) set of near-end signals d_m(t) and set of output residual signals e_mThe number of signals contained in (t) may be equal.

Optionally, the set of echo signals y is estimated based on adaptive filter coefficients w (t) and far-end signal x (t)_m(t) may be calculated as follows:

y_m(t)＝w(t)^Tx_m(t)

calculating an output residual signal set e based on the near-end signal d (t) and the estimated echo signal y (t)_m(t) may be calculated as follows:

e_m(t)＝d_m(t)-y_m(t)

updating the adaptive filter coefficients w (t) according to the adaptive filter update step μ, the far-end signal x (t), the output residual signal e (t) may be updated as follows:

the steps performed by the adaptive filter module 410, the echo cancellation module 420, the update module 430 and the convergence module 440 can refer to the corresponding steps 201 and 203 or 301 and 304 in the aforementioned embodiments, and will not be described herein.

The present application further provides an echo cancellation system, comprising: a memory for storing instructions executable by the processor; and a processor for executing the instructions to implement any of the echo cancellation methods described above.

Fig. 5 illustrates a system block diagram of an echo cancellation system according to an embodiment of the present application. The echo cancellation system 500 may include an internal communication bus 501, a Processor (Processor)502, a Read Only Memory (ROM)503, a Random Access Memory (RAM)504, and a communication port 505. When implemented on a personal computer, the echo cancellation system may also include a hard disk 507. The internal communication bus 501 may enable data communication among the components of the echo cancellation system 500. The processor 502 may make the determination and issue the prompt. In some embodiments, the processor 502 may be comprised of one or more processors. The communication port 505 may enable the echo cancellation system 500 to communicate data with the outside. In some embodiments, the echo cancellation system 500 may send and receive information and data from a network through the communication port 505. The echo cancellation system 500 may also include various forms of program storage units and data storage units such as a hard disk 507, a Read Only Memory (ROM)503 and a Random Access Memory (RAM)504, capable of storing various data files for computer processing and/or communication, and possibly program instructions for execution by the processor 502. The processor executes these instructions to implement the main parts of the method. The results processed by the processor are communicated to the user device through the communication port and displayed on the user interface.

The echo cancellation method described above may be implemented as a computer program, stored in the hard disk 507, and recorded in the processor 502 to be executed so as to implement any echo cancellation method in the present application.

The present application also provides a computer readable medium having stored thereon computer program code which, when executed by a processor, implements any of the echo cancellation methods described above.

When embodied as a computer program, the echo cancellation method may also be stored in a computer readable storage medium as an article of manufacture. For example, computer-readable storage media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD)), smart cards, and flash memory devices (e.g., electrically Erasable Programmable Read Only Memory (EPROM), card, stick, key drive). In addition, various storage media described herein can represent one or more devices and/or other machine-readable media for storing information. The term "machine-readable medium" can include, without being limited to, wireless channels and various other media (and/or storage media) capable of storing, containing, and/or carrying code and/or instructions and/or data.

It should be understood that the above-described embodiments are illustrative only. The embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, and/or other electronic units designed to perform the functions described herein, or a combination thereof.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing disclosure is by way of example only, and is not intended to limit the present application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. The processor may be one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), digital signal processing devices (DAPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or a combination thereof. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips … …), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD) … …), smart cards, and flash memory devices (e.g., card, stick, key drive … …).

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Although the present application has been described with reference to the present specific embodiments, it will be recognized by those skilled in the art that the foregoing embodiments are merely illustrative of the present application and that various changes and substitutions of equivalents may be made without departing from the spirit of the application, and therefore, it is intended that all changes and modifications to the above-described embodiments that come within the spirit of the application fall within the scope of the claims of the application.