CN109451398B - Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system - Google Patents
Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system Download PDFInfo
- Publication number
- CN109451398B CN109451398B CN201811365085.8A CN201811365085A CN109451398B CN 109451398 B CN109451398 B CN 109451398B CN 201811365085 A CN201811365085 A CN 201811365085A CN 109451398 B CN109451398 B CN 109451398B
- Authority
- CN
- China
- Prior art keywords
- signal
- adaptive filter
- band
- sub
- full
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
- H04R3/02—Circuits for transducers, loudspeakers or microphones for preventing acoustic reaction, i.e. acoustic oscillatory feedback
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2430/00—Signal processing covered by H04R, not provided for in its groups
Abstract
The application relates to an acoustic feedback cancellation device, comprising: the first input end of the full-band adaptive filter is connected with the output end of the audio processing module, the output end of the full-band adaptive filter is connected with the output end of the audio acquisition module, the first input end of the filter updating module is connected with the output end of the audio processing module, the second input end of the filter updating module is connected with the output end of the audio acquisition module, and the output end of the filter updating module is connected with the second input end of the full-band adaptive filter; the full-band adaptive filter generates an acoustic feedback prediction signal based on the processed audio signal output by the audio processing module; the filter updating module updates the filtering parameters of the full-band adaptive filter based on the audio input signal, the acoustic feedback prediction signal and the processed audio signal. With the above apparatus, the generation of the acoustic feedback prediction signal by the full band adaptive filter can be used to cancel the acoustic feedback signal, thereby suppressing the acoustic feedback phenomenon. An acoustic feedback cancellation method and an audio processing system are also provided.
Description
Technical Field
The present application relates to the field of signal processing technologies, and in particular, to an acoustic feedback cancellation apparatus, an acoustic feedback cancellation method, and an audio processing system.
Background
With the development of the signal processing field, in systems such as hearing aids, portable microphones and the like based on acquisition, processing, amplification and playing, the sound of the playing end is easily fed back to the acquisition end due to factors such as too large amplification gain or phase coincidence, and howling is further caused. The presence of howling greatly affects the use experience of the device. In conventional designs, the maximum value of the amplification gain must be limited in order to prevent the occurrence of the acoustic feedback phenomenon, but such operation may limit the performance of the device.
Disclosure of Invention
In view of the above, it is desirable to provide an acoustic feedback cancellation apparatus, an acoustic feedback cancellation method, and an audio processing system that can solve the above-described technical problems.
An acoustic feedback cancellation device, comprising:
the first input end of the full-band adaptive filter is connected with the output end of the audio processing module, the output end of the full-band adaptive filter is connected with the output end of the audio acquisition module, the first input end of the filter updating module is connected with the output end of the audio processing module, the second input end of the filter updating module is connected with the output end of the audio acquisition module, and the output end of the filter updating module is connected with the second input end of the full-band adaptive filter;
the full-band adaptive filter is used for generating an acoustic feedback prediction signal based on the processed audio signal output by the audio processing module;
and the filter updating module is used for updating the filtering parameters of the full-band adaptive filter based on the audio input signal, the acoustic feedback prediction signal and the processed audio signal.
The acoustic feedback elimination device comprises a full-band adaptive filter and a filter updating module, wherein the full-band adaptive filter generates an acoustic feedback signal based on a processed audio signal output by the audio processing module, and the filter updating module updates the full-band adaptive filter based on an audio input signal and an acoustic feedback prediction signal. By the above-mentioned acoustic feedback cancellation apparatus generating a prediction signal of acoustic feedback using the full-band adaptive filter, the return of the acoustic feedback prediction signal to the audio processing system can be used to cancel the acoustic feedback signal, thereby suppressing the acoustic feedback phenomenon.
In one embodiment, the filter updating module generates a current time difference signal between the audio input signal and the acoustic feedback signal at the current time; and updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time.
In one embodiment, the filter update module comprises a subband analysis filter bank, a subband adaptive filter, and a frequency domain sampling module;
the subband analysis filter bank is used for acquiring the processed signal at the current moment and the current moment difference signal, and performing subband decomposition processing on the processed signal at the current moment and the current moment difference signal to obtain a processed subband signal at the current moment and a current moment difference subband signal; updating the sub-band self-adaptive filter based on the sub-band signal processed at the current moment and the current moment difference sub-band signal;
and the frequency domain sampling module is used for carrying out frequency domain sampling on the sub-band adaptive filter and transforming the sub-band adaptive filter to a time domain to obtain the full-band adaptive filter.
In one embodiment, the frequency domain sampling module comprises: the device comprises a sub-band adaptive filter frequency domain matrix determining module, a full-band adaptive filter frequency domain vector determining module and a full-band adaptive filter determining module;
the frequency domain matrix determining module of the sub-band adaptive filter is used for calculating the frequency domain matrix of the sub-band adaptive filter based on the sub-band signal processed at the current moment and the difference value sub-band signal at the current moment;
the frequency domain vector determining module of the full-band adaptive filter is used for taking the specific position of the frequency domain matrix of the sub-band adaptive filter by a frequency domain sampling method and combining the specific position into a frequency domain vector of the full-band adaptive filter;
and the full-band adaptive filter determining module is used for transforming the frequency domain vector of the full-band adaptive filter to the time domain to obtain the full-band adaptive filter.
In one embodiment, the subband analysis filterbank is further configured to: performing down-sampling processing on the sub-band signal processed at the current moment and the current moment difference sub-band signal by adopting a down-sampling factor to obtain a sub-band down-sampled signal processed at the current moment and a current moment difference sub-band down-sampled signal;
and updating the sub-band self-adaptive filter based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment.
In one embodiment, the subband analysis filter bank updates the subband adaptive filter by using an NLMS algorithm based on the processed subband down-sampled signal at the current time and the current time difference subband down-sampled signal.
In one embodiment, the prototype of the full band adaptive filter is a FIR filter with an initial value of all zeros.
An acoustic feedback cancellation method, comprising:
acquiring a current-time audio input signal acquired and output by an audio acquisition device at the current time;
determining a current time difference signal between the current time audio input signal and the acoustic feedback prediction signal according to the acoustic feedback prediction signal output by the full-band adaptive filter;
performing audio processing on the difference signal at the current moment to obtain a processed signal at the current moment; the audio processing comprises amplification processing;
and updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time, and updating the acoustic feedback prediction signal output by the full-band adaptive filter according to the processed signal at the current time.
In one embodiment, updating the filter parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time includes:
performing sub-band decomposition on the difference signal at the current moment to obtain a difference sub-band signal at the current moment, and performing sub-band decomposition on the processed signal at the current moment to obtain a processed sub-band signal at the current moment;
performing down-sampling processing on the difference sub-band signal at the current moment to obtain a down-sampled signal of the difference sub-band at the current moment; performing down-sampling processing on the sub-band signal processed at the current moment to obtain a sub-band down-sampled signal processed at the current moment;
updating the sub-band self-adaptive filter based on the sub-band down-sampling signal of the difference value at the current moment and the sub-band down-sampling signal processed at the current moment;
and updating the filtering parameters of the full-band adaptive filter based on the sub-band adaptive filter.
An audio processing system comprises an audio acquisition module, an audio processing module, an audio output module and the acoustic feedback elimination equipment.
Drawings
FIG. 1 is a schematic diagram of an acoustic feedback cancellation apparatus in one embodiment;
FIG. 2 is a block diagram of a filter update module according to an embodiment;
FIG. 3 is a flow diagram of an acoustic feedback cancellation method in one embodiment;
FIG. 4 is a schematic diagram illustrating a process of updating filter parameters of a full-band adaptive filter based on a difference signal at a current time and a processed signal at the current time according to an embodiment;
FIG. 5 is a block diagram of an audio processing system according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The present application provides an acoustic feedback cancellation device, as shown in fig. 1, comprising: a full band adaptive filter 110 and a filter update module 120. The first input end of the full band adaptive filter 110 is connected to the output end of the audio processing module, the output end is connected to the output end of the audio acquisition module, the first input end of the filter updating module 120 is connected to the output end of the audio processing module, the second input end is connected to the output end of the audio acquisition module, and the output end is connected to the second input end of the full band adaptive filter 110.
The adaptive filter is a filter that changes parameters and structure of the filter using an adaptive algorithm according to a change in environment. In general, the structure of the adaptive filter is not changed. While the coefficients of the adaptive filter are time-varying coefficients updated by the adaptive algorithm. I.e. its coefficients are automatically adapted continuously to a given signal to obtain a desired response. The most important feature of the adaptive filter is that it can operate efficiently in unknown environments and can track the time-varying characteristics of the input signal.
A full band adaptive filter 110 for generating an acoustic feedback prediction signal based on the processed audio signal output by the audio processing module.
In this embodiment, a full-band adaptive filter obtains a processed audio signal output by an audio processing module in an audio processing system, and generates an acoustic feedback prediction signal based on the processed audio signal; further, the acoustic feedback prediction signal is returned to the audio processing system for canceling the acoustic feedback signal. The acoustic feedback refers to a phenomenon that sound emitted by an audio output module of the audio processing system returns to an audio acquisition module of the audio processing system, and the sound emitted from the audio output module may return to the audio acquisition module through different ways. Due to the existence of acoustic feedback, the final sound field has poor frequency response characteristics, and a comb filter effect can be generated; howling will occur when such feedback satisfies the oscillation condition, and howling can occur at many frequency points. In this embodiment, a signal processed and output by the audio processing system is referred to as a processed audio signal, and a signal of acoustic feedback predicted by the full band adaptive filter is referred to as an acoustic feedback prediction signal. In one embodiment, the audio output module may be an electroacoustic conversion device such as a speaker and a digital-to-analog converter.
In one embodiment, the prototype of the full band adaptive filter is a FIR adaptive filter with an initial value of all zeros. In this embodiment, an input end of the full band adaptive filter for performing acoustic feedback prediction is referred to as a first input end, and an input end of the full band adaptive filter for performing filter parameter updating is referred to as a second input end. Further, the full band adaptive filter is a time domain adaptive filter, and the delay can be reduced by canceling the acoustic feedback by the full band adaptive filter.
A filter updating module 120, configured to update the filtering parameters of the full-band adaptive filter based on the audio input signal, the acoustic feedback prediction signal, and the processed audio signal.
In one embodiment, the filter update module 120 is configured to: generating a current time difference signal between the current time audio input signal and the acoustic feedback signal; and updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time.
The audio input signal at the current moment is an audio signal collected by an audio collection module of the audio processing system at the current moment; the difference signal at the current moment is the difference signal between the audio input signal at the current moment and the acoustic feedback signal. In this embodiment, after the filter updating module updates the filter parameters of the full-band adaptive filter, the obtained full-band adaptive filter is the full-band adaptive filter at the next time of the current time.
The acoustic feedback elimination device comprises a full-band adaptive filter and a filter updating module, wherein the full-band adaptive filter generates an acoustic feedback signal based on a processed audio signal output by the audio processing module, and the filter updating module updates the full-band adaptive filter based on an audio input signal and an acoustic feedback prediction signal. By the above-mentioned acoustic feedback cancellation apparatus generating a prediction signal of acoustic feedback using the full-band adaptive filter, the return of the acoustic feedback prediction signal to the audio processing system can be used to cancel the acoustic feedback signal, thereby suppressing the acoustic feedback phenomenon.
In one embodiment, as shown in fig. 2, the filter update module includes a subband analysis filter bank 121, a subband adaptive filter 122, and a frequency domain sampling module 123.
The subband analysis filter bank 121 is configured to obtain a processed signal at the current time and a current time difference signal, and perform subband decomposition processing on the processed signal at the current time and the current time difference signal to obtain a processed subband signal at the current time and a current time difference subband signal; the subband adaptive filter 122 is updated based on the processed subband signal at the current time and the difference subband signal at the current time.
Wherein, in one embodiment, the subband analysis filter bank 121 is a complex sinusoidally modulated subband analysis filter bank, which is a set of filters obtained by a prototype filter by different complex sinusoids modulation. Carrying out sub-band decomposition on the processed signal at the current moment by using a complex sine modulation sub-band analysis filter group to obtain a processed sub-band signal at the current moment; and performing sub-band decomposition on the difference signal at the current moment to obtain a difference sub-band signal at the current moment. Further, the complex sinusoidally modulated subband analysis filter bank updates the subband adaptive filter 122 based on the processed subband signal at the current time and the difference subband signal at the current time.
In a specific embodiment, the processed signal at the current time is denoted as u (n), the difference signal at the current time is denoted as e (n), and the complex sinusoidal modulation subband analysis filter group u (n), e (n) are decomposed to obtain the subband signal u (n)i(n)、ei(n) comprises:
wherein i belongs to [0, M-1 ]]，
i is the subband number, M represents the total number of subbands, and L represents the length of the subband analysis prototype filter.
In one embodiment, the subband analysis filterbank is configured to: performing down-sampling processing on the sub-band signal processed at the current moment and the current moment difference sub-band signal by adopting a down-sampling factor to obtain a sub-band down-sampled signal processed at the current moment and a current moment difference sub-band down-sampled signal; and updating the sub-band self-adaptive filter based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment.
In the field of digital signal processing, down-sampling, i.e., down-sampling, is a multi-rate digital signal processing technique or a process for reducing a signal sampling rate, and is generally used to reduce a data transmission rate or a data size. The down-sampling factor (often denoted by the symbol "M") is typically an integer or rational number greater than 1. This factor expresses that the sampling period becomes M times the original, or equivalently that the sampling rate becomes 1/M times the original. Since a reduction in the sampling rate causes a compression of the spectrum, it is necessary to ensure that aliasing does not occur at a low sampling frequency by using a filter, and to ensure that the nyquist sampling theorem remains true.
Further, in an embodiment, the subband analysis filter bank includes a first subband analysis filter bank and a second subband analysis filter bank, where the first subband analysis filter bank is configured to perform subband decomposition and downsampling on the processed signal at the current time to obtain a processed subband downsampled signal at the current time; and the second sub-band analysis filter bank is used for carrying out sub-band decomposition and down-sampling processing on the difference signal at the current moment to obtain a sub-band down-sampled signal processed at the current moment.
In this embodiment, the subband signals are down-convertedSampling to obtain
Wherein D is a down-sampling factor, which may specifically be:
wherein M is Q D, Q is Z+。
In one embodiment, the subband analysis filter bank updates the subband adaptive filter by using an NLMS algorithm based on the processed subband down-sampled signal at the current time and the current time difference subband down-sampled signal.
Further, in one embodiment, updating the subband adaptive filter using the NLMS algorithm comprises:
wherein the content of the first and second substances,
in one embodiment, μ ═ 0.25 and δ ═ 106D is 2, M is 32, L is 64, and P is 16. The updating of the filter on each sub-band can be carried out in parallel, which is beneficial to being realized by using a large-scale integrated circuit.
And the frequency domain sampling module 123 is configured to perform frequency domain sampling on the sub-band adaptive filter, and transform the sub-band adaptive filter to a time domain to obtain a full-band adaptive filter.
In one embodiment, the frequency domain sampling module comprises: the device comprises a sub-band adaptive filter frequency domain matrix determining module, a full-band adaptive filter frequency domain vector determining module and a full-band adaptive filter determining module.
And the frequency domain matrix determining module of the sub-band adaptive filter is used for calculating the frequency domain matrix of the sub-band adaptive filter based on the sub-band signal processed at the current moment and the difference value sub-band signal at the current moment.
Further, the calculating the subband adaptive filter frequency domain matrix comprises:
wherein the content of the first and second substances,
and the frequency domain vector determining module of the full-band adaptive filter is used for taking the specific position of the frequency domain matrix of the sub-band adaptive filter by a frequency domain sampling method and combining the specific position into the frequency domain vector of the full-band adaptive filter.
Furthermore, by a frequency domain sampling method, specific positions of the frequency domain matrix of the sub-band adaptive filter are taken and combined into a frequency domain vector of the full-band adaptive filter, which comprises the following steps:
wherein, WF∈CP×1。
And the full-band adaptive filter determining module is used for transforming the frequency domain vector of the full-band adaptive filter to the time domain to obtain the full-band adaptive filter.
The adaptive filter determined by the full-band adaptive filter determination module is the full-band adaptive filter at the next moment of the current moment.
Further, transforming the frequency domain vector of the full-band adaptive filter to the time domain to obtain the full-band adaptive filter, comprising:
wherein the content of the first and second substances,
the acoustic feedback elimination equipment is used for eliminating acoustic feedback, and only the sub-band analysis processing is needed to be carried out on the signals, so that the processing complexity can be simplified.
In one embodiment, the present application provides an acoustic feedback cancellation method, as shown in fig. 3, including steps S310 to S340.
Step S310, acquiring the audio input signal at the current moment acquired and output by the audio acquisition equipment at the current moment.
In one embodiment, the audio acquisition device may be an acoustic-electric conversion device such as a microphone and a digital-to-analog converter. The audio input signal comprises an external audio signal and an acoustic feedback signal which are acquired by the audio acquisition module. The acoustic feedback signal is an audio signal which is in the audio signal output by the audio output module, reaches through the outside air, object reflection and the like, and is collected by the audio collection module.
Step S320, determining a current time difference signal between the current time audio input signal and the acoustic feedback prediction signal according to the acoustic feedback prediction signal output by the full band adaptive filter.
The acoustic feedback prediction signal is an acoustic feedback signal predicted by a full-band adaptive filter, and further may be an acoustic feedback prediction signal obtained by predicting based on a processed signal output by an audio processing module. The difference signal at the current moment is the difference between the audio input signal at the current moment and the acoustic feedback prediction signal, and ideally, the difference signal at the current moment should be close to the audio signal without the acoustic feedback prediction signal, that is, the external audio signal at the current moment collected by the audio collection module.
In one embodiment, the time difference signal may be determined by providing a subtractor between the output of the full band adaptive filter and the output of the audio acquisition module, the subtractor generating the time difference signal. It is understood that in other embodiments, the determination of the difference signal at the current time may be implemented in other manners.
Step S330, audio processing is carried out on the difference signal at the current moment, and a processed signal at the current moment is obtained.
Wherein the audio processing comprises an amplification process. The processed signal at the current moment is an audio signal output by the audio processing module. In this embodiment, the audio signal processed by the audio processing module may be a current time audio input signal acquired and output by the audio signal, or a current time difference signal between the current time audio input signal and a current time acoustic feedback prediction signal. The audio input signal at the current moment may contain an acoustic feedback signal, so that the audio processing module processes the audio input signal at the current moment and outputs a processed signal at the current moment, which is used for updating the filtering parameters of the full-band adaptive filter. And the audio processing module is used for processing the current time difference signal and then outputting the processed signal at the current time, namely the processed signal after eliminating the acoustic feedback signal, and sending the processed signal to the audio output module for outputting.
And step S340, updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time, and updating the acoustic feedback prediction signal output by the full-band adaptive filter according to the processed signal at the current time.
And updating the filtering parameters of the full-band adaptive filter at the next moment of the current moment based on the current moment difference signal and the processed signal at the current moment. And further, after updating, obtaining the full-band adaptive filter at the next moment of the current moment, wherein the full-band adaptive filter at the next moment generates an acoustic feedback prediction signal at the next moment according to the processed signal at the current moment.
In this embodiment, the full-band adaptive filter is updated by using the time domain error, and it is ensured that the full-band adaptive filter is finally converged to the time domain optimal solution, so that the processing delay of the acoustic feedback cancellation can be reduced by the acoustic feedback prediction signal generated by the full-band adaptive filter.
According to the acoustic feedback elimination method, the audio processing equipment generates a difference signal at the current moment according to the audio input signal and the acoustic feedback prediction signal at the current moment, outputs the processed signal at the current moment after audio processing is carried out on the difference signal at the current moment, and sends the processed signal at the current moment to the audio output equipment for audio output. The full-band adaptive filter is time-domain, so that the output error signal of the full-band adaptive filter can reduce the processing delay of acoustic feedback elimination to the maximum extent, and the suppression effect is greatly improved in the acoustic feedback elimination processing.
In one embodiment, the filter parameters of the full-band adaptive filter are updated based on the current time difference signal and the processed signal at the current time, as shown in fig. 4, including steps S341 to S344.
Step S341, performing subband decomposition on the current time difference signal to obtain a current time difference subband signal, and performing subband decomposition on the processed signal at the current time to obtain a processed subband signal at the current time.
Step 342, performing down-sampling processing on the difference sub-band signal at the current moment to obtain a difference sub-band down-sampled signal at the current moment; and performing down-sampling processing on the sub-band signal processed at the current moment to obtain a sub-band down-sampled signal processed at the current moment.
In one embodiment, the subband decomposition process and the downsampling process are performed by a subband analysis filter bank. Specifically, the subband decomposition processing and the down-sampling processing can be completed by a complex sine modulation subband analysis filter bank.
Step S343, based on the sub-band down-sampled signal of the difference value at the current moment and the sub-band down-sampled signal processed at the current moment, the sub-band adaptive filter is updated.
In one embodiment, an NLMS iterative algorithm is used to perform iterative updates to the subband adaptive filters.
In step S344, the filter parameters of the full band adaptive filter are updated based on the sub-band adaptive filter.
In one embodiment, after the subband adaptive filter is obtained, the subband adaptive filter is transformed to the time domain by a frequency domain sampling method to obtain a full-band adaptive filter at the next time of the current time. Further, the frequency domain sampling method comprises the steps of: calculating a frequency domain matrix of the sub-band adaptive filter; according to a frequency domain sampling method, extracting specific positions of a frequency domain matrix of the sub-band adaptive filter to combine into a frequency domain vector of the full-band adaptive filter; and then transforming the frequency domain vector of the full-band adaptive filter to the time domain to obtain the full-band adaptive filter at the next moment of the current moment.
In a specific embodiment, the above-mentioned acoustic feedback cancellation method is implemented in an audio processing system having an acoustic feedback cancellation function. In this embodiment, the audio acquisition module is taken as a microphone and the audio output module is taken as a speaker. The method comprises the following steps:
at the present moment, the microphone collects an external audio signal and a sound feedback signal, a signal obtained by superposing the two signals is an audio input signal, and the audio input signal is sent to the audio processing module to be amplified and subjected to other processing operations to obtain a processed signal. Meanwhile, a full-band adaptive filter in the acoustic feedback device generates an acoustic feedback prediction signal based on the processed signal. The acoustic feedback signal is an audio signal which reaches the microphone through air, object reflection and the like in the audio signal played by the loudspeaker and is collected by the microphone.
And generating a difference signal of the current moment based on the audio input signal and the acoustic feedback prediction signal, amplifying the difference signal of the current moment by the audio processing module to obtain a processed signal of the next moment, and sending the processed signal of the next moment to the loudspeaker for playing.
Meanwhile, the filter updating module for eliminating acoustic feedback updates the filtering parameters of the full-band adaptive filter based on the obtained current time difference signal and the processed signal at the current time, so as to obtain the full-band adaptive filter at the next time.
And at the next moment, the microphone collects the external audio signal and the acoustic feedback signal at the next moment, the external audio signal and the acoustic feedback signal are recorded as the audio input signal at the next moment, and the audio input signal at the next moment is processed by the audio processing module to obtain the processed signal at the next moment. Meanwhile, the full-band adaptive filter at the next moment generates an acoustic feedback prediction signal at the next moment based on the processed signal at the next moment.
The acoustic feedback in the audio processing system is eliminated by the acoustic feedback elimination method, the full-band adaptive filter is in a time domain, and an acoustic feedback prediction signal is generated by the full-band adaptive filter, so that the delay of acoustic feedback elimination processing can be reduced; in addition, the updating part of the filter only needs to perform subband analysis processing on the signal, and the processing complexity of acoustic feedback elimination can be simplified.
In one embodiment, the present application further provides an audio processing system, which includes an audio acquisition module, an audio processing module, an audio output module, and the above-mentioned acoustic feedback cancellation device.
The audio acquisition module is used for acquiring audio, the audio processing module is used for carrying out audio processing on audio signals, outputting the processed signals, and sending the processed signals to the audio output module for audio output. The audio signal processed by the audio processing module includes a current-time audio input signal acquired and output by the audio signal, or a difference signal between the current-time audio input signal and a current-time acoustic feedback prediction signal.
The audio input signal at the current moment may contain an acoustic feedback signal, so that the audio processing module processes the audio input signal at the current moment and outputs a processed signal at the current moment, which is used for updating the filtering parameters of the full-band adaptive filter. And the audio processing module is used for processing the current time difference signal and then outputting the processed signal at the current time, namely the processed signal after eliminating the acoustic feedback signal, and sending the processed signal to the audio output module for outputting.
The audio processing may include, among other things, amplification processing, noise reduction processing, and so forth.
The filter updating part of the audio processing system only needs to analyze and process the audio signal subband, thereby simplifying the processing complexity; in addition, an error signal of the acoustic feedback elimination part is generated by a time domain filter, so that the processing delay of the acoustic feedback elimination is reduced to the maximum extent, and the acoustic feedback suppression effect is improved; the sub-band update part of the filter can be calculated in parallel, which is beneficial to being realized by using a large-scale integrated circuit.
For specific limitations of the audio processing system, reference may be made to the above limitations of the acoustic feedback cancellation device, which are not described in detail herein.
In a specific embodiment, as shown in fig. 5, the schematic diagram of the audio processing system in this embodiment is a schematic diagram, which includes an audio acquisition module, an audio processing module, an audio output module, and an acoustic feedback cancellation device, in this embodiment, the acoustic feedback cancellation device includes: full band adaptive filter wnA first sub-band analysis filter bank, a second sub-band analysis filter bank, a sub-band adaptive filter wniAnd a frequency domain sampling module.
Wherein, the signal s (n) is an external audio signal acquired by an audio acquisition module composed of an acoustic-electric conversion device such as a microphone and an analog-to-digital converter; the signal u (n) is a processed audio signal processed and amplified by the audio processing module q (n); the signal d (n) is an audio signal emitted by an audio output module consisting of an electroacoustic conversion device such as a loudspeaker and a digital-to-analog converter, and reaches an acoustic feedback signal acquired by an audio acquisition module through external air or object reflection and other ways; the signal q (n) is a superimposed signal of the acoustic feedback signal d (n) and the external audio signal s (n); the signal y (n) is an acoustic feedback prediction signal obtained by predicting the processed signal by the acoustic feedback elimination equipment; the signal e (n) is a difference signal of the current time, i.e. the difference signal between the audio input signal and the acoustic feedback prediction signal. Where the symbol n is a time variable that increases with time.
The audio processing system includes an acoustic feedback cancellation and filter update section. Wherein the acoustic feedback eliminating section inputs u (n) into wnAnd obtaining y (n), subtracting q (n) from y (n) to obtain a signal e (n) after acoustic feedback elimination, inputting e (n) into the audio processing module to obtain u (n +1), and sending u (n +1) to the audio output module for output.
A filter updating part for performing subband decomposition on u (n) by the first subband analysis filter group to obtain ui(n) using the down-sampling factor D to pair ui(n) down-sampling to obtain ui D(m); similarly, e is obtained by performing subband decomposition on the second subband analysis filter group e (n)i(n) using the down-sampling factor D to ei(n) down-sampling to obtain ei D(m) of the reaction mixture. In this embodiment, the filter bank that performs subband decomposition and downsampling on u (n) is referred to as a first subband analysis filter bank, and the filter bank that performs subband decomposition and downsampling on e (n) is referred to as a second subband analysis filter bank.
Subband filter w by NLMS iterative algorithmniCarrying out iterative update to obtain w(n+1)iThen the sub-band filter w is filtered by the frequency domain sampling method(n+1)iAnd transforming to the time domain to obtain the full-band adaptive filter at the n +1 th moment.
Further, the specific steps of the filter updating part may include: carrying out sub-band decomposition on u (n) and e (n) by a complex sine modulation sub-band analysis filter group to obtain a sub-band signal ei(n),ui(n)，i∈[0,M-1]I is the subband number and M is the total number of subbands.
Where L is the subband analysis prototype filter length.
Then, the sub-band signals are down-sampled to obtain
D is a down-sampling factor, M is Q D, Q is formed by Z+；
Subband filter w by NLMS iterative algorithmniAnd (3) performing iterative updating:
wherein the content of the first and second substances,
μ,δ∈R+。
in one embodiment, μ ═ 0.25 and δ ═ 106，D＝2，M＝32，L＝64，P＝16。
Finally, the sub-band filter w is filtered by a frequency domain sampling method(n+1)i，i∈[0,M-1]Transform to time domain filter wn+1The method comprises the following specific steps:
calculating a frequency domain matrix of the sub-band adaptive filter:
according to a frequency domain sampling method, extracting specific positions of a frequency domain matrix of the sub-band adaptive filter to combine into a frequency domain vector of the full-band adaptive filter:
and transforming the frequency domain vector of the full-band filter to the time domain to obtain the full-band adaptive filter at the n +1 th moment:
the full band adaptive filter at time n +1 may generate a new acoustic feedback prediction signal based on the processed signal at time n + 1.
It should be understood that although the steps in the flowcharts of fig. 3 and 4 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 3 and 4 may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least some of the sub-steps or stages of other steps.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (6)
1. An acoustic feedback cancellation device, comprising: a full band adaptive filter and a filter update module;
the first input end of the full-band adaptive filter is connected with the output end of the audio processing module, the output end of the full-band adaptive filter is connected with the output end of the audio acquisition module, the first input end of the filter updating module is connected with the output end of the audio processing module, the second input end of the filter updating module is connected with the output end of the audio acquisition module, and the output end of the filter updating module is connected with the second input end of the full-band adaptive filter;
the full-band adaptive filter is used for generating an acoustic feedback prediction signal based on the processed signal at the current moment output by the audio processing module; the full-band adaptive filter finally converges to a time domain optimal solution;
the filter updating module is used for updating the filtering parameters of the full-band adaptive filter based on the current-time audio input signal, the acoustic feedback prediction signal and the current-time processed signal; the filter updating module comprises a sub-band analysis filter bank, a sub-band self-adaptive filter and a frequency domain sampling module; the subband analysis filter bank is used for acquiring the processed signal at the current moment and the current moment difference signal, and performing subband decomposition processing on the processed signal at the current moment and the current moment difference signal to obtain a processed subband signal at the current moment and a current moment difference subband signal; updating the sub-band adaptive filter based on the sub-band signal after the current time processing and the current time difference sub-band signal; the frequency domain sampling module is used for carrying out frequency domain sampling on the sub-band adaptive filter and transforming the sub-band adaptive filter to a time domain to obtain the full-band adaptive filter;
the frequency domain sampling module comprises: the device comprises a sub-band adaptive filter frequency domain matrix determining module, a full-band adaptive filter frequency domain vector determining module and a full-band adaptive filter determining module; the sub-band adaptive filter frequency domain matrix determining module is used for calculating a sub-band adaptive filter frequency domain matrix based on the sub-band signal processed at the current moment and the current moment difference sub-band signal; the frequency domain vector determining module of the full-band adaptive filter is used for taking the specific position of the frequency domain matrix of the sub-band adaptive filter by a frequency domain sampling method and combining the specific position into a frequency domain vector of the full-band adaptive filter; the full-band adaptive filter determining module is used for transforming the frequency domain vector of the full-band adaptive filter to the time domain to obtain the full-band adaptive filter;
the subband analysis filter bank is further configured to: performing down-sampling processing on the sub-band signal processed at the current moment and the current moment difference sub-band signal by adopting a down-sampling factor to obtain a sub-band down-sampled signal processed at the current moment and a current moment difference sub-band down-sampled signal; updating the sub-band adaptive filter based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment;
the sub-band analysis filter bank updates the sub-band adaptive filter by adopting an NLMS algorithm based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment;
the audio input signal at the current moment is an audio signal collected by an audio collection module of the audio processing system at the current moment; the current time difference signal is a difference signal of the current time audio input signal and the acoustic feedback signal; after the filter updating module updates the filter parameters of the full-band adaptive filter, the obtained full-band adaptive filter is the full-band adaptive filter at the next moment of the current moment;
the frequency domain vector determining module of the full-band adaptive filter takes the specific position of the frequency domain matrix of the sub-band adaptive filter by a frequency domain sampling method to combine into the frequency domain vector of the full-band adaptive filter, and the frequency domain vector is expressed by the following formula:
wherein M represents the total number of subbands, D is a down-sampling factor, M is Q and D, and Q belongs to Z+；
WFRepresenting a full-band adaptive filter frequency domain vector; k represents the number of subbands, k belongs to [0, M-1 ]]；n∈[0，P/M-1](ii) a Idx represents a specific position of the frequency domain matrix of the sub-band adaptive filter and an index of the frequency domain matrix of the sub-band adaptive filter; wk SBRepresenting a frequency domain vector obtained by performing frequency domain transformation on the kth subband filter; cP×1Where C represents a complex field, CP×1A complex field representing a matrix of P rows and 1 columns; z + represents a positive integer set; p represents the length of the full band adaptive filter;
the full-band adaptive filter determining module is configured to transform the frequency domain vector of the full-band adaptive filter to a time domain to obtain the full-band adaptive filter, and is represented by the following formula:
wherein, wn+1(m) represents a full band adaptive filter, n represents an nth time instant; exp is an exponential operation with a natural number as a base number;
updating the sub-band adaptive filter by adopting an NLMS algorithm, comprising the following steps:
wherein the content of the first and second substances,
μ，δ∈R+；μ＝0.25，δ＝106，D＝2，M＝32，L＝64，P＝16；
wherein, Ui DRepresenting a time domain signal obtained after the ith subband signal is subjected to down-sampling and amplification processing by the audio processing module, wherein U represents a time domain vector amplified by the audio processing module; u (n) represents a time domain signal of the current subband signal at the nth moment after being amplified by the audio processing module;
ei Drepresenting the ith subband signal, obtaining an error signal after down sampling, and e representing the error signal of the adaptive filter; h represents the conjugate transpose of the matrix; r + represents a positive real number set。
2. The acoustic feedback cancellation apparatus of claim 1, wherein the filter update module generates a time of day difference signal between the time of day audio input signal and the acoustic feedback signal; and updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time.
3. The acoustic feedback cancellation apparatus of claim 1, wherein the prototype of the full band adaptive filter is a FIR filter with an initial value of all zeros.
4. An acoustic feedback cancellation method, comprising:
acquiring a current-time audio input signal acquired and output by an audio acquisition device at the current time;
determining a current time difference signal between the current time audio input signal and the acoustic feedback prediction signal according to the acoustic feedback prediction signal output by the full-band adaptive filter;
performing audio processing on the difference signal at the current moment to obtain a processed signal at the current moment; the audio processing comprises amplification processing; the full-band adaptive filter finally converges to a time domain optimal solution;
updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time, and updating the acoustic feedback prediction signal output by the full-band adaptive filter according to the processed signal at the current time;
acquiring the processed signal at the current moment and the current moment difference signal, and performing sub-band decomposition processing on the processed signal at the current moment and the current moment difference signal to obtain a processed sub-band signal at the current moment and a current moment difference sub-band signal; updating a sub-band adaptive filter based on the sub-band signal after the current time processing and the current time difference sub-band signal; sampling the frequency domain of the sub-band adaptive filter, and transforming the sub-band adaptive filter to the time domain to obtain the full-band adaptive filter;
calculating a frequency domain matrix of the sub-band adaptive filter based on the sub-band signal processed at the current moment and the current moment difference sub-band signal; by a frequency domain sampling method, taking specific positions of the frequency domain matrix of the sub-band adaptive filter, and combining the specific positions into a frequency domain vector of the full-band adaptive filter; transforming the frequency domain vector of the full-band adaptive filter to a time domain to obtain the full-band adaptive filter;
performing down-sampling processing on the sub-band signal processed at the current moment and the current moment difference sub-band signal by adopting a down-sampling factor to obtain a sub-band down-sampled signal processed at the current moment and a current moment difference sub-band down-sampled signal; updating the sub-band adaptive filter based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment;
updating the sub-band adaptive filter by adopting an NLMS algorithm based on the sub-band down-sampled signal processed at the current moment and the sub-band down-sampled signal of the difference value at the current moment;
the audio input signal at the current moment is an audio signal collected by an audio collection module of the audio processing system at the current moment; the current time difference signal is a difference signal of the current time audio input signal and the acoustic feedback signal; updating the filtering parameters of the full-band adaptive filter based on the current time difference signal and the processed signal at the current time, wherein the obtained full-band adaptive filter is the full-band adaptive filter at the next moment of the current time;
and (2) by a frequency domain sampling method, taking the specific position of the frequency domain matrix of the sub-band adaptive filter, combining the specific position into a frequency domain vector of the full-band adaptive filter, and expressing the vector by the following formula:
wherein M represents the total number of subbands, D is a down-sampling factor, M is Q and D, and Q belongs to Z+；
WFRepresenting a full-band adaptive filter frequency domain vector; k represents the number of subbands, k belongs to [0, M-1 ]]；n∈[0，P/M-1](ii) a Idx represents a specific position of the frequency domain matrix of the sub-band adaptive filter and an index of the frequency domain matrix of the sub-band adaptive filter; wk SBRepresenting a frequency domain vector obtained by performing frequency domain transformation on the kth subband filter; cP×1Where C represents a complex field, CP×1A complex field representing a matrix of P rows and 1 columns; z + represents a positive integer set; p represents the length of the full band adaptive filter;
transforming the frequency domain vector of the full-band adaptive filter to a time domain to obtain the full-band adaptive filter, which is expressed by the following formula:
wherein, wn+1(m) represents a full band adaptive filter, n represents an nth time instant; exp is an exponential operation with a natural number as a base number;
updating the sub-band adaptive filter by adopting an NLMS algorithm, comprising the following steps:
wherein the content of the first and second substances,
μ，δ∈R+；μ＝0.25，δ＝106，D＝2，M＝32，L＝64，P＝16；
wherein, Ui DRepresents a time domain signal obtained after the ith subband signal is subjected to down-sampling and amplification processing by the audio processing module, and U represents the amplification of the audio processing moduleA processed time domain vector; u (n) represents a time domain signal of the current subband signal at the nth moment after being amplified by the audio processing module;
ei Drepresenting the ith subband signal, obtaining an error signal after down sampling, and e representing the error signal of the adaptive filter; h represents the conjugate transpose of the matrix; r + represents a positive real number set.
5. The method of claim 4, wherein updating filter parameters of a full-band adaptive filter based on the current-time difference signal and the current-time processed signal further comprises:
performing down-sampling processing on the current time difference sub-band signal to obtain a current time difference sub-band down-sampled signal; performing down-sampling processing on the sub-band signal processed at the current moment to obtain a sub-band down-sampled signal processed at the current moment;
updating the sub-band adaptive filter based on the sub-band down-sampling signal of the difference value at the current moment and the sub-band down-sampling signal processed at the current moment;
updating the filter parameters of the full-band adaptive filter based on the sub-band adaptive filter.
6. An audio processing system comprising an audio acquisition module, an audio processing module, an audio output module, and an acoustic feedback cancellation device according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811365085.8A CN109451398B (en) | 2018-11-16 | 2018-11-16 | Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811365085.8A CN109451398B (en) | 2018-11-16 | 2018-11-16 | Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109451398A CN109451398A (en) | 2019-03-08 |
| CN109451398B true CN109451398B (en) | 2021-03-19 |
Family
ID=65552444
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811365085.8A Active CN109451398B (en) | 2018-11-16 | 2018-11-16 | Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109451398B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112565981B (en) * | 2021-02-20 | 2021-06-15 | 深圳市智听科技有限公司 | Howling suppression method, howling suppression device, hearing aid, and storage medium |
| CN113593516B (en) * | 2021-07-22 | 2024-04-02 | 中国船舶集团有限公司第七一一研究所 | Active vibration and noise control method, system, storage medium and ship |
| CN114157951A (en) * | 2021-11-26 | 2022-03-08 | 歌尔科技有限公司 | Active noise reduction circuit and device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1272982A (en) * | 1998-06-22 | 2000-11-08 | Ati国际有限公司 | Idle signals and echo cancellation |
| CN1499809A (en) * | 2002-11-04 | 2004-05-26 | 华为技术有限公司 | Echo eliminator and method for evaluating echo |
| CN102185991A (en) * | 2011-03-01 | 2011-09-14 | 杭州华三通信技术有限公司 | Echo cancellation method, system and device |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE69731573T2 (en) * | 1996-02-09 | 2005-03-31 | Texas Instruments Inc., Dallas | Noise reduction arrangement |
| JP3099870B2 (en) * | 1996-07-23 | 2000-10-16 | 日本電気株式会社 | Acoustic echo canceller |
| US6947549B2 (en) * | 2003-02-19 | 2005-09-20 | The Hong Kong Polytechnic University | Echo canceller |
| EP2148526B1 (en) * | 2008-07-24 | 2020-08-19 | Oticon A/S | Spectral content modification for robust feedback channel estimation |
| CN103840794B (en) * | 2014-03-26 | 2017-02-08 | 南京大学 | Active control method for simplifying sub-band structure non-secondary path |
| CN106454642B (en) * | 2016-09-23 | 2019-01-08 | 佛山科学技术学院 | Adaptive sub-band audio feedback suppression methods |
| CN106601266A (en) * | 2017-02-24 | 2017-04-26 | 喜大（上海）网络科技有限公司 | Echo cancellation method, device and system |
| CN107291663A (en) * | 2017-06-12 | 2017-10-24 | 华侨大学 | The variable step suppressed applied to acoustic feedback normalizes sub-band adaptive filtering method |
-
2018
- 2018-11-16 CN CN201811365085.8A patent/CN109451398B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1272982A (en) * | 1998-06-22 | 2000-11-08 | Ati国际有限公司 | Idle signals and echo cancellation |
| CN1499809A (en) * | 2002-11-04 | 2004-05-26 | 华为技术有限公司 | Echo eliminator and method for evaluating echo |
| CN102185991A (en) * | 2011-03-01 | 2011-09-14 | 杭州华三通信技术有限公司 | Echo cancellation method, system and device |
Non-Patent Citations (1)
| Title |
|---|
| 自适应啸叫抑制算法的研究与DSP实现;陈丹艳;《中国优秀硕士学位论文全文数据库 信息科技辑》;20160315;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109451398A (en) | 2019-03-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10950213B1 (en) | Hybrid active noise cancellation filter adaptation | |
| US9818424B2 (en) | Method and apparatus for suppression of unwanted audio signals | |
| CN1719516B (en) | Adaptive filter device and adaptive filtering method | |
| CN109451398B (en) | Acoustic feedback cancellation apparatus, acoustic feedback cancellation method, and audio processing system | |
| JP5091948B2 (en) | Blind signal extraction | |
| US20210375255A1 (en) | Hybrid active noise control system | |
| WO2009110578A1 (en) | Dereverberation apparatus, dereverberation method, dereverberation program, and recording medium | |
| EP1638079B1 (en) | Method and system for active noise cancellation | |
| CN111988708A (en) | Single-microphone-based howling suppression method and device | |
| TWI819478B (en) | Hearing device with end-to-end neural network and audio processing method | |
| JP5153389B2 (en) | Acoustic signal processing device | |
| Gan et al. | Howling noise cancellation in time–frequency domain by deep neural networks | |
| KR100848789B1 (en) | Postprocessing method for removing cross talk | |
| CN113611279A (en) | Active noise reduction system and noise reduction earphone | |
| JP4527654B2 (en) | Voice communication device | |
| Mollaei | Hardware implementation of adaptive filters | |
| JP5524316B2 (en) | Parameter estimation apparatus, echo cancellation apparatus, parameter estimation method, and program | |
| CN113347536B (en) | Acoustic feedback suppression algorithm based on linear prediction and sub-band adaptive filtering | |
| Zhang et al. | Neural network augmented kalman filter for robust acoustic howling suppression | |
| US20240054988A1 (en) | Reduced Complexity Implementation for Acoustic Noise Canceling | |
| JP4729072B2 (en) | Echo erasing device, echo erasing method, echo erasing program, and recording medium | |
| Biradar et al. | Implementation of an Active Noise Cancellation Technique using Deep Learning | |
| CN116405836B (en) | Microphone tuning method and system based on Internet | |
| EP4054210A1 (en) | A hearing device comprising a delayless adaptive filter | |
| CN109905811A (en) | A kind of method and device of economical acoustic feedback control |
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 | ||
| CP02 | Change in the address of a patent holder |
Address after: 519000 No. 333, Kexing Road, Xiangzhou District, Zhuhai City, Guangdong Province Patentee after: ZHUHAI JIELI TECHNOLOGY Co.,Ltd. Address before: Floor 1-107, building 904, ShiJiHua Road, Zhuhai City, Guangdong Province Patentee before: ZHUHAI JIELI TECHNOLOGY Co.,Ltd. |
|
| CP02 | Change in the address of a patent holder |