CN113241084B - Echo cancellation method, device and equipment - Google Patents
Echo cancellation method, device and equipment Download PDFInfo
- Publication number
- CN113241084B CN113241084B CN202110412101.XA CN202110412101A CN113241084B CN 113241084 B CN113241084 B CN 113241084B CN 202110412101 A CN202110412101 A CN 202110412101A CN 113241084 B CN113241084 B CN 113241084B
- Authority
- CN
- China
- Prior art keywords
- coefficient
- signal
- echo
- adaptive filter
- convergence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M9/00—Arrangements for interconnection not involving centralised switching
- H04M9/08—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic
- H04M9/082—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic using echo cancellers
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L2021/02082—Noise filtering the noise being echo, reverberation of the speech
Abstract
The application discloses a method, a device and equipment for echo cancellation, wherein the method comprises the following steps: acquiring a far-end voice signal and a first echo signal; obtaining an initial coefficient of an adaptive filter based on the far-end voice signal and the first echo signal; responding to the switching of the audio output equipment from the first equipment to the second equipment, and acquiring a second echo signal; acquiring a target coefficient of the adaptive filter according to a second device coefficient and an initial coefficient of the adaptive filter and the second echo signal; and echo cancellation is carried out on the near-end voice signal through the adaptive filter based on the target coefficient. The method provided by the embodiment of the application can accelerate the convergence speed of the adaptive filter, improve the echo cancellation efficiency and improve the user experience when the audio output equipment is switched.
Description
Technical Field
The embodiment of the application relates to the technical field of audio processing, in particular to a method, a device and equipment for echo cancellation.
Background
During the voice communication process, a far-end voice signal generated by a far-end caller during far-end speech is collected by a far-end microphone, transmitted to a near end through network transmission and broadcasted by a near-end loudspeaker, and the broadcasted voice signal is collected by the near-end microphone after being reflected and transmitted to the far end, so that the far-end caller hears own voice through the far-end loudspeaker, namely, echo is generated. Echo interferes with normal speech, so echo cancellation is a critical step in voice speech.
In the related art, an adaptive filter is used for echo cancellation, wherein the adaptive filter updates coefficients by a Normalized Least Mean Square (NLMS) adaptive algorithm, so that the adaptive filter converges, and echo cancellation is performed by the converged adaptive filter.
However, the echo cancellation method in the related art is only suitable for the situation that the audio output device is kept stable, and when the audio output device changes during a call, the convergence speed of the adaptive filter in the related art is slow, and the echo cancellation efficiency is low, so that the echo is obvious, and the call quality and the user experience are affected.
Disclosure of Invention
The embodiment of the application provides a method, a device and equipment for echo cancellation, which are used for reducing the convergence time of a self-adaptive filter, improving the efficiency of echo cancellation and further improving the user experience when audio output equipment is changed.
In a first aspect, an embodiment of the present application provides a method for echo cancellation, where the method includes: acquiring a far-end voice signal and a first echo signal, wherein the first echo signal is an echo signal when an audio output device is a first device; obtaining initial coefficients of an adaptive filter based on the far-end speech signal and the first echo signal; responding to the audio output equipment, namely the first equipment is switched into second equipment, and acquiring a second echo signal, wherein the second echo signal is an echo signal when the audio output equipment is the second equipment; acquiring a target coefficient of the adaptive filter according to a second device coefficient of the adaptive filter, the initial coefficient and the second echo signal, wherein the second device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device; and echo cancellation is carried out on the near-end voice signal through the self-adaptive filter based on the target coefficient.
In one possible implementation manner, the obtaining a target coefficient of the adaptive filter according to the second device coefficient of the adaptive filter, the initial coefficient, and the second echo signal includes: determining convergence of the initial coefficient based on the second echo signal, the convergence of the initial coefficient indicating a magnitude of an estimated first error signal of a first echo estimation signal and the second echo signal obtained by the adaptive filter based on the initial coefficient, the estimated first error signal being inversely related to the convergence of the initial coefficient; determining convergence of the second device coefficients based on the second echo signal, the convergence of the second device coefficients indicating a magnitude of an estimated second error signal, the estimated second error signal being an error signal of a second echo estimate signal obtained by the adaptive filter based on the second device coefficients and the second echo signal, the estimated second error signal being inversely related to the convergence of the second device coefficients; and taking the second device coefficient as the target coefficient based on the convergence of the second device coefficient being greater than the convergence of the initial coefficient.
In one possible implementation, the method further includes: based on the convergence of the second device coefficient being less than the convergence of the initial coefficient, treating the initial coefficient as the target coefficient.
In one possible implementation, the determining convergence of the second device coefficient based on the second echo signal includes: acquiring the estimated magnitude of a third error signal based on the second device coefficient, wherein the third error signal is an error signal between a third echo estimation signal obtained by an auxiliary filter based on the second device coefficient and the second echo signal; and taking the estimated magnitude of the third error signal as the convergence of the second device coefficient.
In a possible implementation manner, the second device coefficient is a coefficient obtained after the adaptive filter converges when the audio output device is the second device last time, or a preset coefficient of the adaptive filter when the audio output device is the second device.
In one possible implementation, the method further includes: determining a first device coefficient of the adaptive filter based on the initial coefficient, the first device coefficient being a reference coefficient corresponding to the adaptive filter when the audio output device is the first device.
In one possible implementation manner, the obtaining initial coefficients of an adaptive filter based on the far-end speech signal and the first echo signal includes: obtaining a fourth error signal based on the first echo signal; obtaining the initial coefficient based on the far-end speech signal and the fourth error signal.
In one possible implementation, the performing echo cancellation on the near-end speech signal by the adaptive filter based on the target coefficient includes: obtaining a fifth error signal based on a target echo estimation signal and the second echo signal, the target echo estimation signal being obtained by the adaptive filter based on the target coefficient; acquiring a coefficient after the adaptive filter converges based on the fifth error signal and the target coefficient; and performing echo cancellation on the near-end voice signal through the adaptive filter based on the converged coefficient.
In a second aspect, an embodiment of the present application provides an apparatus for echo cancellation, where the apparatus includes: the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a far-end voice signal and a first echo signal, and the first echo signal is an echo signal when the audio output equipment is first equipment; a second obtaining module, configured to obtain an initial coefficient of an adaptive filter based on the far-end speech signal and the first echo signal; a third obtaining module, configured to obtain a second echo signal in response to the audio output device being switched from the first device to a second device, where the second echo signal is an echo signal when the audio output device is the second device; a fourth obtaining module, configured to obtain a target coefficient of the adaptive filter according to a second device coefficient of the adaptive filter and the initial coefficient, where the second device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device; and the echo cancellation module is used for performing echo cancellation on the near-end voice signal through the self-adaptive filter based on the target coefficient.
In a possible implementation manner, the fourth obtaining module is configured to determine a convergence of the initial coefficient based on the second echo signal, where the convergence of the initial coefficient indicates a magnitude of an estimated first error signal, where the first error signal is an error signal of a first echo estimation signal and a second echo signal obtained by the adaptive filter based on the initial coefficient, and the estimated first error signal is inversely related to the convergence of the initial coefficient; determining convergence of the second device coefficients based on the second echo signal, the convergence of the second device coefficients indicating a magnitude of an estimated second error signal, the estimated second error signal being an error signal of a second echo estimate signal obtained by the adaptive filter based on the second device coefficients and the second echo signal, the estimated second error signal being inversely related to the convergence of the second device coefficients; and taking the second device coefficient as the target coefficient based on the convergence of the second device coefficient being greater than the convergence of the initial coefficient.
In a possible implementation manner, the fourth obtaining module is further configured to use the initial coefficient as the target coefficient based on that the convergence of the second device coefficient is smaller than that of the initial coefficient.
In a possible implementation manner, the fourth obtaining module is configured to obtain a magnitude of an estimated third error signal based on the second device coefficient, where the third error signal is an error signal between a third echo estimation signal obtained by an auxiliary filter based on the second device coefficient and the second echo signal; and taking the estimated magnitude of the third error signal as the convergence of the second device coefficient.
In a possible implementation manner, the second device coefficient is a coefficient obtained after the adaptive filter converges when the audio output device is the second device last time, or a preset coefficient of the adaptive filter when the audio output device is the second device.
In a possible implementation manner, the second obtaining module is configured to obtain a fourth error signal based on the first echo signal; obtaining the initial coefficient based on the far-end speech signal and the fourth error signal.
In a possible implementation manner, the echo cancellation module is configured to obtain a fifth error signal based on a target echo estimation signal and the second echo signal, where the target echo estimation signal is obtained by the adaptive filter based on the target coefficient; acquiring a coefficient after the adaptive filter is converged based on the fifth error signal and the target coefficient; and echo cancellation is carried out on the near-end voice signal through the self-adaptive filter based on the converged coefficient.
In a third aspect, an embodiment of the present application provides a computer device, where the computer device includes a processor and a memory, where the memory stores at least one instruction, and the at least one instruction, when executed by the processor, implements the method for echo cancellation according to any one of the above first aspects.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which at least one instruction is stored, and when executed, the at least one instruction implements the method for echo cancellation according to any one of the above first aspects
In a fifth aspect, an embodiment of the present application provides a computer program (product), where the computer program (product) includes: computer program code which, when executed by a computer, causes the computer to perform the method of echo cancellation in the above aspects.
According to the embodiment of the application, when the audio output device is switched from the first device to the second device, the target coefficient is determined based on the initial coefficient of the adaptive filter and the coefficient of the second device, so that the adaptive filter performs echo cancellation on the basis of the target coefficient, the convergence time of the adaptive filter after the first device is switched to the second device is effectively shortened, the echo cancellation efficiency is improved, and the user experience is further improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic illustration of an implementation environment provided by an embodiment of the present application;
fig. 2 is a flowchart of a method for echo cancellation according to an embodiment of the present application;
fig. 3 is a schematic diagram of an apparatus for echo cancellation according to an embodiment of the present application;
fig. 4 is a schematic diagram of a method for echo cancellation according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an echo cancellation device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an echo cancellation device according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
In the related art, the adaptive filter on the communication device performs echo cancellation based on the coefficient, and when the audio output device changes, the adaptive filter re-converges and further performs echo cancellation. Therefore, the embodiment of the present application provides an echo cancellation method, which can accelerate convergence of an adaptive filter when an audio output device changes, and improve echo cancellation efficiency.
Referring to fig. 1, a schematic diagram of an implementation environment of a method provided in an embodiment of the present application is shown. The implementation environment may include: an echo cancellation device 11, an output device 22, and an input device 33. Wherein the echo cancellation device 11 includes the filter 111, optionally, the filter 111 may be any one or more of an adaptive filter and an auxiliary filter, and a relationship between the adaptive filter and the auxiliary filter and an operation method will be described in the following embodiments. The input device 33 inputs the voice signal to the echo cancellation device 11, and the echo cancellation device 11 processes the voice signal and outputs the voice signal through the output device 22. Wherein the echo cancellation device 11 processes the speech signal through a filter 111.
Based on the above-mentioned implementation environment shown in fig. 1, please refer to fig. 2, which shows a flowchart of a method for providing echo cancellation according to an embodiment of the present application, and the method can be applied to the echo cancellation device 11 shown in fig. 1. As shown in fig. 2, the method provided by the embodiment of the present application may include the following steps 101-105.
The far-end speech signal is input through a far-end audio input device (e.g., a microphone) and transmitted to the near-end, where the echo cancellation device may capture the far-end speech signal. After the far-end voice signal is transmitted to the near-end, the far-end voice signal generates an echo signal through an echo signal channel of the near-end.
The first echo signal is an echo signal when the audio output device is the first device, and optionally, the first echo signal may be acquired by collecting from an echo signal channel.
Further, the far-end speech signal and the echo signal may be processed, including: and respectively performing framing, windowing and Fourier transform on the far-end voice signal and the echo signal to obtain corresponding frequency domain signals. It should be noted that, in the subsequent steps, the far-end speech signal and the echo signal are still used to refer to their corresponding frequency domain signals, respectively. That is to say, the far-end speech signal mentioned in the embodiment of the present application may be an original signal transmitted from a far-end speech device, or may be a frequency domain signal obtained through processing such as framing, windowing, and fourier transform. The echo signal may be an original echo signal generated by a far-end speech signal through a near-end echo device, or may be a frequency domain signal obtained through processing such as framing, windowing, fourier transform, and the like.
The adaptive filter may obtain the initial coefficients by converging before the audio output device is not switched. In one possible implementation, obtaining the initial coefficients of the adaptive filter based on the far-end speech signal and the first echo signal may include the following sub-steps 1021 and 1022.
1021. A fourth error signal is obtained based on the first echo signal.
The first echo signal is an echo signal when the audio output device is the first device. In one possible implementation manner, acquiring the fourth error signal based on the first echo signal includes: acquiring a fourth echo estimation signal based on the far-end voice signal; a fourth error signal is obtained based on the fourth echo estimate signal and the first echo signal.
Optionally, based on the far-end speech signal, the fourth echo estimation signal may be obtained by an adaptive filter, and optionally, the adaptive filter may calculate the echo estimation signal using an adaptive filtering algorithm. Illustratively, obtaining the fourth error signal based on the fourth echo estimate signal and the first echo signal comprises: a difference between the first echo signal and the fourth echo estimate signal is calculated and used as a fourth error signal. Illustratively, the first echo signal is denoted as d (n), and the fourth echo estimation signal is denoted as
The fourth error signal is denoted as e (n), and e (n) is calculated according to the following formula:
1022. initial coefficients of the adaptive filter are obtained based on the far-end speech signal and the fourth error signal.
In a possible implementation manner, the obtaining of the initial coefficient of the adaptive filter according to the NLMS algorithm based on the far-end speech signal and the fourth error signal includes: calculating to obtain far-end voice signal energy based on the far-end voice signal; and iteratively acquiring an initial coefficient through an NLMS algorithm based on the far-end voice signal, the far-end voice signal energy and the fourth error signal.
In one example, let the far-end speech signal be denoted as x (n), the fourth error signal be denoted as e (n), and the energy of the far-end speech signal be denoted as PfarAnd iterating according to the NLMS algorithm according to the following formula until the self-adaptive filter converges to obtain an initial coefficient:
where ω is a filter coefficient, n is an iteration number, μ is an update step coefficient for adjusting the adaptive iteration step, and δ is a positive number with a small value for avoiding a divisor of 0.
Optionally, μ is updated according to the following formula:
wherein, PfarIs the energy of the far-end speech signal, mumax、μmin、PminAnd PmaxAnd g are reference values preset in the echo cancellation device and can be obtained based on experience. Wherein, mumaxFor maximum step-size coefficient of reference, muminIs the minimum step-size coefficient of reference, PminFor reference speech signal minimum energy, PmaxIs the maximum energy of the reference speech signal.
Optionally, after obtaining the initial coefficients, the method further includes: monitoring a double-end conversation state; based on the double-end-call state indication that only the far-end voice signal exists, the initial coefficient is updated according to the method for obtaining the initial coefficient, and the updated initial coefficient is still used as the initial coefficient to perform the subsequent steps of the embodiment of the application.
As can be seen from the above process, the obtaining of the initial coefficient is a dynamic process, and when the adaptive filter is in a stable working state (i.e. the coefficient on the adaptive filter is not changed any more, i.e. the adaptive filter is converged), and the audio output device is not changed, the coefficient on the adaptive filter at this time is considered as the initial coefficient.
In the audio output process, the audio output device may change, and in this case, the echo cancellation device needs to monitor the audio output device and obtain the switching condition of the audio output device in time. Thus, in a possible implementation manner, before acquiring the second echo signal in response to the audio output device being switched from the first device to the second device, the method further includes: an audio output device is monitored.
Illustratively, monitoring an audio output device includes the steps of: 10311. the echo cancellation device monitors the audio output device according to the reference frequency to obtain a monitoring result; 10312. based on the change of the monitoring result, the echo cancellation device generates a trigger signal for switching the audio output device. The reference frequency may be set based on experience, and power consumption by the monitoring audio output device may be reduced by the limitation of the reference frequency.
For example, the audio output device is monitored at a frequency of once monitoring for 2 seconds, and when the monitoring result of the audio output device is changed from the first device to the second device, the echo cancellation device generates a trigger signal for switching the first device to the second device, where the trigger signal is used to trigger the process of adjusting the filter coefficients and performing echo cancellation as described in steps 103 to 105.
For another example, the audio output device is monitored according to the frequency of once monitoring for 2 seconds, if the audio output device is switched from the first device to the second device within 2 seconds and then from the second device to the first device, the monitoring result indicates that the audio output device is not switched, so that the switching of the audio output device occurring in a very short time can be ignored, and the power consumption caused by monitoring the audio output device is reduced.
The first device may represent a device originally used for audio output and the second device may represent a device currently used for audio output. The device for audio output is not limited in the embodiments of the present application, and illustratively, the first device is a speaker, and the second device is a headphone.
And after the audio output equipment is monitored to be switched from the first equipment to the second equipment, responding to the monitoring result, and acquiring a second echo signal, wherein the second echo signal is the echo signal when the audio output equipment is the second equipment.
And 104, acquiring a target coefficient of the adaptive filter according to the second device coefficient and the initial coefficient of the adaptive filter and the second echo signal.
The second device coefficient of the adaptive filter is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device. In the case where the audio output device is the second device, the adaptive filter can be made to converge quickly using the reference coefficient. The convergence of the adaptive filter refers to a process that the adaptive filter adjusts coefficients until the coefficients are kept stable based on the far-end voice signal, the near-end voice signal and the echo signal, and the converged adaptive filter can perform effective echo cancellation.
Alternatively, the second device coefficient may be a coefficient obtained after the adaptive filter converges the last time the audio output device was the second device. Illustratively, the coefficient obtained by the NLMS algorithm the last time the audio output device was the second device is taken as the second device coefficient, and the second device coefficient is stored.
Alternatively, the second device coefficient may be a coefficient of the adaptive filter when the preset audio output device is the second device. For example, in the primary echo cancellation, a coefficient that enables the adaptive filter to converge quickly in the case where the audio output device is the second device is preset based on experience.
The target coefficient of the adaptive filter is a coefficient obtained by the adaptive filter again by the method provided by the embodiment of the application after the audio output device is switched from the first device to the second device, and the adaptive filter further iterates the coefficient on the basis of the target coefficient and executes the subsequent echo cancellation step, so that the convergence rate of the adaptive filter can be increased and the echo cancellation efficiency can be improved.
In one possible implementation manner, obtaining the target coefficient of the adaptive filter according to the second device coefficient, the initial coefficient and the second echo signal of the adaptive filter includes: determining convergence of the initial coefficient based on the second echo signal; determining convergence of the second device coefficient based on the second echo signal; and taking the second device coefficient as the target coefficient based on the convergence of the second device coefficient being greater than the convergence of the initial coefficient.
The convergence of the initial coefficient indicates the magnitude of the estimated first error signal, the first error signal is the error signal of the first echo estimation signal and the second echo signal obtained by the adaptive filter based on the initial coefficient, and the estimated convergence of the first error signal and the initial coefficient is inversely correlated, i.e. the larger the estimated first error signal is, the smaller the convergence of the initial coefficient is.
Accordingly, the convergence of the second device coefficient indicates the magnitude of the estimated second error signal, the second error signal is an error signal of the second echo estimation signal and the second echo signal obtained by the adaptive filter based on the second device coefficient, and the estimated convergence of the second error signal and the second device coefficient is inversely related, that is, the larger the estimated second error signal is, the smaller the convergence of the second device coefficient is.
The magnitude of the estimated error signal obtained in the process of obtaining the convergence of the coefficient is a prediction or estimation of the magnitude of the error signal to be obtained by the coefficient.
When the convergence of the second device coefficient is larger than the initial coefficient, it is shown that the estimated situation at this time is: the second error signal obtained by the adaptive filter based on the second device coefficients will be smaller than the first error signal obtained by the adaptive filter based on the initial coefficients, i.e. the convergence of the adaptive filter using the second device coefficients will be better than the convergence using the initial coefficients. In order to improve the efficiency of echo cancellation, the stored second device coefficient is used as the target coefficient, and the subsequent steps of adaptive filter convergence and echo cancellation are performed.
Optionally, the method further comprises: and taking the initial coefficient as the target coefficient based on the convergence of the second device coefficient being smaller than the convergence of the initial coefficient.
When the convergence of the second device coefficient is smaller than that of the initial coefficient, it is assumed that: the second error signal obtained by the adaptive filter based on the second device coefficients will be larger than the first error signal obtained by the adaptive filter based on the initial coefficients, i.e. the convergence of the adaptive filter using the initial coefficients will be better than the convergence using the second device coefficients. In order to improve the efficiency of echo cancellation, the initial coefficient is used as the target coefficient, and the subsequent steps of adaptive filter convergence and echo cancellation are carried out.
In order to intuitively obtain a comparison result of the convergence of the initial coefficient and the convergence of the second device, the embodiment of the application further obtains the comparison result of the convergence of the initial coefficient and the convergence of the second device by comparing a predicted first error signal obtained by the adaptive filter based on the initial coefficient and a predicted third error signal obtained by the auxiliary filter based on the second device coefficient. Illustratively, the auxiliary filter may be one of the same filters as the adaptive filter. The auxiliary filter may also be a filter that is only used to estimate the error signal magnitude but does not have the actual convergence and echo cancellation functions.
In one possible implementation, determining convergence of the second device coefficient based on the second echo signal includes: acquiring the estimated magnitude of a third error signal based on the second device coefficient, wherein the third error signal is an error signal of a third echo estimation signal and a second echo signal, which are obtained by the auxiliary filter based on the second device coefficient; and taking the estimated magnitude of the third error signal as the convergence of the second device coefficient.
Optionally, the embodiment of the present application further includes: before determining the convergence of the initial coefficient, a first device coefficient of the adaptive filter is determined based on the initial coefficient, wherein the first device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the first device.
When the first device is switched to the second device, the initial coefficient at this time is a coefficient obtained after the adaptive filter converges last time the audio output device was the first device, and thus the initial coefficient may be used as the first device coefficient. After the first device coefficient is determined, the first device coefficient is stored, so that when the second device is switched to the first device, the target coefficient can be obtained through the first device coefficient and the initial coefficient, and further filter convergence and echo cancellation are performed.
And 105, performing echo cancellation on the near-end voice signal through an adaptive filter based on the target coefficient.
In one possible implementation, echo cancellation is performed on a near-end speech signal by an adaptive filter based on a target coefficient, including: acquiring a fifth error signal based on the target echo estimation signal and the second echo signal, wherein the target echo estimation signal is acquired by the adaptive filter based on a target coefficient; acquiring a coefficient after the convergence of the adaptive filter based on the fifth error signal and the target coefficient; and echo cancellation is carried out on the near-end voice signal through the self-adaptive filter based on the converged coefficient.
The adaptive filter may obtain a target echo estimation signal based on the target coefficient, and then calculate a difference between the second echo signal and the target echo estimation signal to obtain a fifth error signal.
Converging the adaptive filter according to the NLMS algorithm based on the fifth error signal and the target coefficient to obtain a coefficient after the adaptive filter is converged; and performing echo cancellation on the near-end voice signal through the adaptive filter based on the converged coefficients.
It should be noted that, in this embodiment of the present application, the near-end speech signal is obtained continuously from the beginning of double-end turn-on, and performing echo cancellation on the near-end speech signal through the adaptive filter based on the converged coefficient refers to performing echo cancellation on the newly obtained near-end speech signal.
Optionally, after performing echo cancellation on the near-end speech signal by using the adaptive filter based on the converged coefficient, the near-end speech signal after echo cancellation may be further processed. Illustratively, the echo-cancelled near-end speech signal is non-linearly processed such that the residual echo is further attenuated.
Optionally, after echo cancellation is performed on the near-end speech signal through the adaptive filter based on the converged coefficient, silence monitoring may be performed, and when silence is monitored, comfort noise may be added to improve user experience. The comfort noise is that under the condition of silence, noise with a very low encoding rate is used for simulating background noise, so that transmission signals are uninterrupted, a user can feel that conversation is continuously on line, and user experience is improved.
According to the embodiment of the application, when the audio output device is switched from the first device to the second device, the target coefficient is determined based on the initial coefficient of the adaptive filter and the coefficient of the second device, so that the adaptive filter performs echo cancellation on the basis of the target coefficient, the convergence time of the adaptive filter after the first device is switched to the second device is effectively shortened, the echo cancellation efficiency is improved, and the user experience is further improved.
Please refer to fig. 3, which illustrates a schematic diagram of an echo cancellation method according to an embodiment of the present application.
201 denotes an audio output device monitoring module, configured to monitor whether an audio output device changes; 202 denotes a parameter register, which is used to store at least but not limited to coefficients when the convergence states of two adaptive filters are good, in this embodiment, the coefficients stored in the parameter register 202 may be coefficients obtained after the convergence of the adaptive filters in different output devices, and this embodiment of the present application uses two parameters as an illustration; 203 represents a coefficient 1 for caching a coefficient obtained after the adaptive filter converges in the state that the system speaker outputs the audio; 204 represents a coefficient 2, which is used for caching a coefficient obtained after the adaptive filter converges in the state that the system earphone outputs the audio frequency; reference numeral 205 denotes an auxiliary filter for reading coefficients from the parameter register when the output environment changes, performing convergence comparison with the adaptive filter, and restoring the coefficients to the adaptive filter if necessary, that is, using the buffered coefficients as target coefficients in the adaptive filter; 206 denotes coefficients read from the parameter register, i.e. buffer coefficients; 207, an adaptive filter for filtering and coefficient updating according to the call state; 208 denotes the coefficients of the adaptive filter for echo cancellation by the adaptive filter.
Taking the example where the initial audio device output device is a speaker, the echo cancellation process includes the following steps.
501. And acquiring an initial coefficient.
The adaptive filter 207 performs fast convergence immediately after the call is connected, and a coefficient obtained after the convergence is used as an initial coefficient. For example, the adaptive filter 207 may iteratively obtain initial coefficients according to the method described above in step 101.
502. An audio output device is monitored.
When the audio output device monitoring module 201 monitors that the audio output device is switched to the headphone, the audio output device monitoring module 201 passes the signal to both the auxiliary filter 205 and the adaptive filter 207.
503. And determining that the audio output equipment is switched from a loudspeaker to an earphone based on the monitoring result, and acquiring a target coefficient according to the coefficient 2 and the initial coefficient.
The auxiliary filter 205 reads the coefficient 2 from the parameter register 202, and the buffer filter coefficient 206 in the auxiliary filter 205 is the coefficient 2, and the coefficient 208 in the adaptive filter 207 is the initial coefficient.
The convergence comparison result between the coefficient 2 and the initial coefficient is obtained by the auxiliary filter 205 and the adaptive filter 207, and for the description of the comparison process, reference may be made to the foregoing embodiment shown in fig. 2, which is not described herein again.
As a result of the comparison, there are the following two cases.
In case one, the convergence of coefficient 2 is greater than the initial coefficient convergence, the adaptive filter 207 stores the initial coefficient at the position of filter coefficient 1 in the parameter register 202, and the auxiliary filter 205 restores coefficient 2 to the adaptive filter 207, that is, stores coefficient 2 as a target coefficient in the adaptive filter 207.
In the second case, the convergence of the coefficient 2 is smaller than the convergence of the initial coefficient, and the adaptive filter 207 stores the initial coefficient at the position of the filter coefficient 1 in the parameter register 202 while setting the initial coefficient as the target coefficient.
504. And carrying out echo cancellation based on the target coefficient.
After obtaining the target coefficient, the adaptive filter 207 further iterates the target coefficient based on the NLMS algorithm, and performs echo cancellation based on the coefficient obtained after iteration.
Taking the example where the initial audio device output device is a headphone, the echo cancellation process includes the following steps.
505. An initial coefficient is obtained.
The adaptive filter 207 converges quickly immediately after the call is connected, and the coefficient obtained after the convergence is used as an initial coefficient. For example, the adaptive filter 207 may iteratively obtain initial coefficients according to the method described above for step 101.
506. An audio output device is monitored.
When the audio output device monitoring module 201 monitors that the audio output device is switched to the speaker, the audio output device monitoring module 201 passes the signal to both the auxiliary filter 205 and the adaptive filter 207.
507. And determining that the audio output equipment is switched from the earphone to the loudspeaker based on the monitoring result, and acquiring a target coefficient according to the coefficient 1 and the initial coefficient.
The auxiliary filter 205 reads coefficient 1 from the parameter register 202, and at this time, the buffer coefficient 206 in the auxiliary filter 205 is coefficient 1, and the coefficient 208 in the adaptive filter 207 is the initial coefficient.
The convergence comparison result between the coefficient 1 and the initial coefficient is obtained by the auxiliary filter 205 and the adaptive filter 207, and for the description of the comparison process, reference may be made to the foregoing embodiment shown in fig. 2, which is not described herein again.
As a result of the comparison, there are the following two cases.
In the first case, the convergence of coefficient 1 is greater than the initial coefficient convergence, the adaptive filter 207 stores the initial coefficient in the position of the filter coefficient 2 in the parameter register 202, and the auxiliary filter 205 restores the coefficient 1 to the adaptive filter 207, that is, stores the coefficient 1 as the target coefficient in the adaptive filter 207.
In case two, the convergence of the coefficient 1 is smaller than the convergence of the initial coefficient, and the adaptive filter 207 stores the initial coefficient in the position of the filter coefficient 2 in the parameter register 202 while setting the initial coefficient as the target coefficient.
508. And performing echo cancellation based on the target coefficient.
After obtaining the target coefficient, the adaptive filter 207 further iterates the target coefficient based on the NLMS algorithm, and performs echo cancellation based on the coefficient obtained after iteration.
It should be noted that, when echo cancellation is performed for the first time, the parameter register may store a preset parameter or a null value.
Please refer to fig. 4, which illustrates a schematic structural diagram of an echo cancellation device according to an embodiment of the present application. As shown, the apparatus comprises: a speaker 302; an echo channel 303; a proximal microphone 306; a double-ended speech detection module 307; an adaptive filter 308 for adaptively filtering the far-end speech signal transmitted to the near-end by an adaptive filtering algorithm; an output device monitoring module 311; a parameter register 312; an auxiliary filter 313, described in detail above in FIG. 3; a non-linear processor and comfort noise generator 315 for further processing the echo-cancelled near-end signal and coping with the environment of the idle voice.
Further, in fig. 4, 301 denotes an input far-end speech signal, denoted by x (n); an echo signal d (n) generated by passing through the echo channel, i.e. 304 in fig. 4, exists in the echo channel 303; 305 represents an input near-end speech signal, denoted as y (n); the echo estimate signal generated by the adaptive filter is noted
309 in fig. 4; 310 is an error signal e (n) calculated by the formula
314 is the echo-cancelled near-end signal y1(n) the calculation formula is y1(n) ═ y (n) + e (n); 316 is the speech signal that is ultimately output to the far-end speaker.
A far-end voice signal x (n) is input through a far-end microphone and transmitted to a near end; the near-end speech signal y (n) is input to the near-end through the microphone 306; the method comprises the steps of respectively performing framing, windowing and Fourier transform on an input far-end voice signal x (n), a near-end voice signal y (n) and an echo signal d (n) acquired by a near end to obtain corresponding frequency domain signals, performing delay estimation on a cached far-end voice signal y (n), and respectively calculating the signal energy of the far-end voice signal and the near-end voice signal.
The double-talk detection module 307 detects a current double-talk state and transmits a signal to the adaptive filter, and if only far-end speech is detected under the condition that the audio output device is not changed, the filter updates the coefficient, and if only near-end speech or double-talk exists, the filter does not update the coefficient.
The output device monitoring module 311 continuously monitors the current audio output device of the system, and transmits the signal when the environment changes, and then continues to execute the echo cancellation method shown in fig. 2.
The adaptive filter 308 passes the echo cancellation error signal e (n) fed back and updates the adaptive filter parameters according to the NLMS algorithm. The process of updating the adaptive filter parameters by the adaptive filter 308 according to the NLMS algorithm may refer to the method for obtaining the initial coefficients shown in fig. 2, which is not described herein again. In addition, the adaptive filter 308 may also buffer coefficients to a parameter register when only far-end speech is present. When the double-talk is recovered to the far-end single talk or the audio output mode is switched from the loudspeaker to the wireless earphone, the convergence condition of the adaptive filter at the moment is compared with the auxiliary filter, if the divergence is serious, the coefficient in the auxiliary filter is restored to the adaptive filter and iterative convergence based on the coefficient is carried out, the specific process refers to the echo cancellation method shown in fig. 2, and the embodiment is not described again.
The parameter register 312 performs a parameter caching operation, wherein the cached parameters include: the coefficient obtained after convergence when the loudspeaker outputs and the coefficient obtained after convergence of the adaptive filter when the wireless earphone outputs.
In addition, the near-end microphone 306 collects near-end voice signals and echo signals and transmits the signals to the system; the adder-subtractor subtracts the echo estimation value from the near-end input signal to obtain the echo-cancelled signal.
And the echo-cancelled signal is continuously transmitted forwards, subsequent operations such as nonlinear processing and the like are carried out, the residual echo is further weakened, and the signal is subjected to operations such as noise cancellation, gain and the like. The comfort noise generator 315 is used to simulate background sounds with comfort noise at a very low encoding rate when the system detects silence.
Please refer to fig. 5, which illustrates a schematic diagram of an echo cancellation apparatus according to an embodiment of the present application. As shown in fig. 5, the apparatus includes: a first obtaining module 401, configured to obtain a far-end voice signal and a first echo signal, where the first echo signal is an echo signal when an audio output device is a first device; a second obtaining module 402, configured to obtain an initial coefficient of the adaptive filter based on the far-end speech signal and the first echo signal; a third obtaining module 403, configured to, in response to the audio output device being switched from the first device to the second device, obtain a second echo signal, where the second echo signal is an echo signal when the audio output device is the second device; a fourth obtaining module 404, configured to obtain a target coefficient of the adaptive filter according to a second device coefficient of the adaptive filter and the initial coefficient, where the second device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device; and an echo cancellation module 405, configured to perform echo cancellation on the near-end speech signal through an adaptive filter based on the target coefficient.
In a possible implementation manner, the fourth obtaining module 404 is configured to determine a convergence of an initial coefficient based on the second echo signal, where the convergence of the initial coefficient indicates a magnitude of an estimated first error signal, the first error signal is an error signal of a first echo estimation signal and a second echo signal obtained by the adaptive filter based on the initial coefficient, and the estimated first error signal is negatively correlated with the convergence of the initial coefficient; determining the convergence of a second device coefficient based on the second echo signal, wherein the convergence of the second device coefficient indicates the magnitude of a predicted second error signal, the second error signal is an error signal of a second echo estimation signal and the second echo signal, which are obtained by the adaptive filter based on the second device coefficient, and the predicted second error signal is negatively correlated with the convergence of the second device coefficient; and taking the second device coefficient as the target coefficient based on the convergence of the second device coefficient being greater than the convergence of the initial coefficient.
In a possible implementation manner, the fourth obtaining module 404 is further configured to use the initial coefficient as the target coefficient based on that the convergence of the second device coefficient is smaller than that of the initial coefficient.
In a possible implementation manner, the fourth obtaining module 404 is configured to obtain a magnitude of an estimated third error signal based on the second device coefficient, where the third error signal is an error signal between a third echo estimation signal obtained by the auxiliary filter based on the second device coefficient and the second echo signal; and taking the estimated magnitude of the third error signal as the convergence of the second device coefficient.
In a possible implementation manner, the second device coefficient is a coefficient obtained after the adaptive filter converges last time when the audio output device is the second device, or a preset coefficient of the adaptive filter when the audio output device is the second device.
In a possible implementation manner, the second obtaining module 402 is configured to obtain a fourth error signal based on the first echo signal; and acquiring initial coefficients based on the far-end voice signal and the fourth error signal.
In a possible implementation manner, the echo cancellation obtaining module 405 is configured to obtain a fifth error signal based on a target echo estimation signal and the second echo signal, where the target echo estimation signal is obtained by the adaptive filter based on a target coefficient; acquiring a coefficient after the convergence of the adaptive filter based on the fifth error signal and the target coefficient; and echo cancellation is carried out on the near-end voice signal through the self-adaptive filter based on the converged coefficient.
Referring to fig. 6, a schematic structural diagram of an echo canceling device according to an embodiment of the present invention is shown, where the echo canceling device includes a processor 1201 and a memory 1202, and the memory 1202 stores at least one instruction. The at least one instruction is configured to be executed by the one or more processors 1201 to implement any of the echo cancellation methods described above.
In an exemplary embodiment, there is also provided a computer-readable storage medium having at least one program code stored therein, the at least one program code being loaded and executed by a processor to cause a computer to implement any of the echo cancellation methods described above.
Alternatively, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, there is also provided a computer program or a computer program product having at least one computer instruction stored therein, the at least one computer instruction being loaded and executed by a processor to cause a computer to implement any of the echo cancellation methods described above.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the module is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. Further, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may also be an electrical, mechanical or other form of connection.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present application.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
It should also be understood that, in the embodiments of the present application, the sequence numbers of the respective processes do not mean the execution sequence, and the execution sequence of the respective processes should be determined by the functions and the inherent logic thereof, and should not constitute any limitation to the implementation process of the embodiments of the present application.
The term "at least one" in this application means one or more, and the term "plurality" in this application means two or more, for example, a plurality of data means two or more data.
It is to be understood that the terminology used in the description of the various described examples herein is for the purpose of describing particular examples only and is not intended to be limiting. As used in the description of the various described examples and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The above description is only exemplary of the present application and is not intended to limit the present application, and any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of echo cancellation, the method comprising:
acquiring a far-end voice signal and a first echo signal, wherein the first echo signal is an echo signal when an audio output device is a first device;
obtaining initial coefficients of an adaptive filter based on the far-end speech signal and the first echo signal;
responding to the audio output equipment switched from the first equipment to the second equipment, and acquiring a second echo signal, wherein the second echo signal is an echo signal when the audio output equipment is the second equipment;
acquiring a target coefficient of the adaptive filter according to a second device coefficient of the adaptive filter, the initial coefficient and the second echo signal, where the second device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device;
and performing echo cancellation on the near-end voice signal through the adaptive filter based on the target coefficient.
2. The method of claim 1, wherein obtaining the target coefficients of the adaptive filter according to the second device coefficients of the adaptive filter, the initial coefficients, and the second echo signal comprises:
determining convergence of the initial coefficient based on the second echo signal, the convergence of the initial coefficient indicating a magnitude of an estimated first error signal of a first echo estimation signal and the second echo signal obtained by the adaptive filter based on the initial coefficient, the estimated first error signal being inversely related to the convergence of the initial coefficient;
determining convergence of the second device coefficient based on the second echo signal, the convergence of the second device coefficient indicating a magnitude of an estimated second error signal, the estimated second error signal being an error signal of a second echo estimation signal obtained by the adaptive filter based on the second device coefficient and the second echo signal, the estimated second error signal being negatively correlated with the convergence of the second device coefficient;
and taking the second device coefficient as the target coefficient based on the convergence of the second device coefficient being greater than the convergence of the initial coefficient.
3. The method of claim 2, further comprising:
based on the convergence of the second device coefficient being less than the convergence of the initial coefficient, treating the initial coefficient as the target coefficient.
4. The method of claim 2, wherein the determining the convergence of the second device coefficient based on the second echo signal comprises:
acquiring the estimated magnitude of a third error signal based on the second device coefficient, wherein the third error signal is an error signal of a third echo estimation signal and the second echo signal, which are obtained by an auxiliary filter based on the second device coefficient;
and taking the estimated magnitude of the third error signal as the convergence of the second device coefficient.
5. The method according to any one of claims 1 to 4, wherein the second device coefficient is a coefficient obtained after the adaptive filter converges last time the audio output device is the second device, or a preset coefficient of the adaptive filter when the audio output device is the second device.
6. The method according to any one of claims 2-4, wherein the method further comprises:
determining a first device coefficient of the adaptive filter based on the initial coefficient, the first device coefficient being a reference coefficient corresponding to the adaptive filter when the audio output device is the first device.
7. The method according to any of claims 1-4, wherein said obtaining initial coefficients of an adaptive filter based on the far-end speech signal and the first echo signal comprises:
obtaining a fourth error signal based on the first echo signal;
obtaining the initial coefficient based on the far-end speech signal and the fourth error signal.
8. The method according to any one of claims 1-4, wherein said performing echo cancellation on the near-end speech signal by the adaptive filter based on the target coefficient comprises:
obtaining a fifth error signal based on a target echo estimation signal and the second echo signal, the target echo estimation signal being obtained by the adaptive filter based on the target coefficient;
acquiring a coefficient after the adaptive filter is converged based on the fifth error signal and the target coefficient;
and performing echo cancellation on the near-end voice signal through the adaptive filter based on the converged coefficient.
9. An apparatus for echo cancellation, the apparatus comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a far-end voice signal and a first echo signal, and the first echo signal is an echo signal when the audio output equipment is first equipment;
a second obtaining module, configured to obtain an initial coefficient of an adaptive filter based on the far-end speech signal and the first echo signal;
a third obtaining module, configured to obtain a second echo signal in response to the audio output device being switched from the first device to a second device, where the second echo signal is an echo signal when the audio output device is the second device;
a fourth obtaining module, configured to obtain a target coefficient of the adaptive filter according to a second device coefficient of the adaptive filter and the initial coefficient, where the second device coefficient is a reference coefficient corresponding to the adaptive filter when the audio output device is the second device;
and the echo cancellation module is used for performing echo cancellation on the near-end voice signal through the self-adaptive filter based on the target coefficient.
10. A computer device comprising a processor and a memory, the memory having stored therein at least one instruction which, when executed by the processor, implements the method of echo cancellation according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110412101.XA CN113241084B (en) | 2021-04-16 | 2021-04-16 | Echo cancellation method, device and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110412101.XA CN113241084B (en) | 2021-04-16 | 2021-04-16 | Echo cancellation method, device and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113241084A CN113241084A (en) | 2021-08-10 |
| CN113241084B true CN113241084B (en) | 2022-07-22 |
Family
ID=77128387
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110412101.XA Active CN113241084B (en) | 2021-04-16 | 2021-04-16 | Echo cancellation method, device and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113241084B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116648856A (en) * | 2021-12-17 | 2023-08-25 | 华为技术有限公司 | IIR filter assembly, audio device and coefficient switching method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09130308A (en) * | 1995-08-25 | 1997-05-16 | At & T Corp | Echo canceler and its operating method |
| CN105791515A (en) * | 2014-12-22 | 2016-07-20 | 青岛海信移动通信技术股份有限公司 | Screen state control method for terminal equipment and terminal equipment |
| CN108965777A (en) * | 2017-08-28 | 2018-12-07 | 北京视联动力国际信息技术有限公司 | A kind of echo cancel method and device |
| CN111199748A (en) * | 2020-03-12 | 2020-05-26 | 紫光展锐(重庆)科技有限公司 | Echo cancellation method, device, equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120140939A1 (en) * | 2010-12-07 | 2012-06-07 | Electronics And Telecommunications Research Institute | Method and device for cancelling acoustic echo |
-
2021
- 2021-04-16 CN CN202110412101.XA patent/CN113241084B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09130308A (en) * | 1995-08-25 | 1997-05-16 | At & T Corp | Echo canceler and its operating method |
| CN105791515A (en) * | 2014-12-22 | 2016-07-20 | 青岛海信移动通信技术股份有限公司 | Screen state control method for terminal equipment and terminal equipment |
| CN108965777A (en) * | 2017-08-28 | 2018-12-07 | 北京视联动力国际信息技术有限公司 | A kind of echo cancel method and device |
| CN111199748A (en) * | 2020-03-12 | 2020-05-26 | 紫光展锐(重庆)科技有限公司 | Echo cancellation method, device, equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 台宏达.语音通信系统中的自适应回声消除技术.《计算机仿真》.2015,(第09期), * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113241084A (en) | 2021-08-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106713570B (en) | Echo cancellation method and device | |
| CN104395957A (en) | A universal reconfigurable echo cancellation system | |
| EP2982101B1 (en) | Noise reduction | |
| CN109273019B (en) | Method for double-talk detection for echo suppression and echo suppression | |
| CN110996203B (en) | Earphone noise reduction method, device and system and wireless earphone | |
| EP3929919A1 (en) | Voice signal processing method and device, apparatus, and readable storage medium | |
| CN110634496B (en) | Double-talk detection method and device, computer equipment and storage medium | |
| CN110992923B (en) | Echo cancellation method, electronic device, and storage device | |
| WO2017085760A1 (en) | Echo canceler and communication device | |
| JP4833343B2 (en) | Echo and noise cancellation | |
| CN110956975A (en) | Echo cancellation method and device | |
| CN109215672B (en) | Method, device and equipment for processing sound information | |
| CN113241084B (en) | Echo cancellation method, device and equipment | |
| CN107786755B (en) | Double-end call detection method and device | |
| US6377682B1 (en) | Robust adaptive filter for use in acoustic and network echo cancellation | |
| WO2019239977A1 (en) | Echo suppression device, echo suppression method, and echo suppression program | |
| CN110021289B (en) | Sound signal processing method, device and storage medium | |
| JP4888262B2 (en) | Call state determination device and echo canceller having the call state determination device | |
| CN115834778A (en) | Echo cancellation method, device, electronic equipment and storage medium | |
| JP4396449B2 (en) | Reverberation removal method and apparatus | |
| US10498389B2 (en) | Echo canceller device and voice telecommunications device | |
| JP3982823B2 (en) | Audio processing apparatus, audio processing method, and audio processing program | |
| JP6180689B1 (en) | Echo canceller apparatus, echo cancellation method, and echo cancellation program | |
| KR102266780B1 (en) | Method and apparatus for reducing speech distortion by mitigating clipping phenomenon and using correlation between microphone input signal, error signal, and far end signal occurring in a voice communication environment | |
| CN113225442B (en) | Method and device for eliminating echo |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221221 Address after: 401121 4-1, No. 6, North Yangliu Road, Dazhulin Street, Liangjiang New District, Yubei District, Chongqing Patentee after: Chongqing wutong Chelian Technology Co.,Ltd. Address before: 100089 area B, 5th floor, block a, 8 Haidian Street, Haidian District, Beijing Patentee before: BEIJING WUTONG CHELIAN TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right |