CN115019763A - Active noise reduction method, device, equipment and medium for voice equipment - Google Patents
Active noise reduction method, device, equipment and medium for voice equipment Download PDFInfo
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- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
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- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17821—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the input signals only
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- G—PHYSICS
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- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17821—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the input signals only
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- G10K11/1785—Methods, e.g. algorithms; Devices
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- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
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Abstract
The invention relates to the field of noise reduction of voice equipment, and discloses an active noise reduction method, device, equipment and medium of the voice equipment. The method comprises the steps of obtaining clean noise information by offsetting the obtained noise information and the last-moment noise reduction information, updating a filter based on a preset LMS algorithm by utilizing the clean noise information and the obtained last-moment residual noise information, receiving the updated filter according to the clean noise information, correspondingly playing noise reduction information by a loudspeaker, offsetting the noise reduction information and the external noise information to obtain new residual noise information, returning and re-executing the steps to continuously update the residual noise information until the residual noise information approaches zero to obtain clean voice information, and solving the problem that the noise in the voice cannot be effectively removed by the existing equipment.
Description
Technical Field
The present invention relates to the field of noise reduction for voice devices, and in particular, to an active noise reduction method, device, and medium for a voice device.
Background
Today, technological development is on a new and more basis, the application of head-mounted voice equipment is more and more extensive, and people use voice equipment to carry out interactive communication, when listening to activities such as music, the noise information of external environment can pass voice equipment and get into the ear, in order to reduce the influence of external noise to the user, except improving in the aspect of the physical mechanism at voice equipment, also can reduce the influence of external noise to voice equipment through voice equipment self adoption method of falling the noise voluntarily.
Disclosure of Invention
The invention mainly aims to solve the technical problem that the existing equipment cannot effectively eliminate noise information.
A first aspect of the present invention provides an active noise reduction method for a speech device, where the speech device includes: the active noise reduction method of the voice equipment comprises the following steps:
acquiring external noise information, noise information acquired by the reference microphone and last-moment residual noise information acquired by the error microphone;
compensating the noise information to obtain clean noise information;
updating the filter based on a preset LMS algorithm by using the clean noise information and the last-moment residual noise information;
receiving the clean noise information according to the updated filter, and correspondingly playing noise reduction information by the loudspeaker;
and offsetting according to the noise reduction information and the external noise information to obtain new residual noise information, and returning and re-executing the steps.
Optionally, in a first implementation manner of the first aspect of the present invention, before the acquiring external noise information, noise information acquired by the reference microphone, last-minute residual noise information acquired by the error microphone, and last-minute noise reduction information transmitted by a preset estimation feedback path, the method further includes:
and performing off-line estimation to obtain a coefficient of a preset estimation feedforward path and a coefficient of a preset estimation feedback path.
Optionally, in a second implementation manner of the first aspect of the present invention, the speech device further includes a white noise generator, the white noise generator is configured to play white noise information, and the performing the off-line estimation to obtain the coefficient of the preset estimated feedforward path and the coefficient of the preset estimated feedback path includes:
receiving the white noise information according to the reference microphone to obtain first white noise information, obtaining second white noise information through a preset estimation feedback path according to the white noise information, and mutually offsetting the first white noise information and the second white noise information to obtain a first difference value;
receiving the white noise information according to the error microphone to obtain third white noise information, respectively obtaining fourth white noise information through a preset estimation feedforward path according to the white noise information, and mutually offsetting the third white noise information and the fourth white noise information to obtain a second difference value;
and processing the first difference value and the second difference value based on the LMS algorithm to respectively obtain a coefficient of a preset estimation feedback path and a coefficient of a preset estimation feedforward path.
Optionally, in a third implementation manner of the first aspect of the present invention, the external noise information is obtained by transmitting external noise through an acoustic path, and the noise information includes the noise reduction information and the external noise that are respectively collected by the reference microphone and played by the speaker.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the compensating the noise information to obtain clean noise information includes:
obtaining last-moment noise reduction information transmitted by the estimation feedback path;
and compensating the noise information according to the noise reduction information at the last moment, and offsetting the noise reduction information in the noise information.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the updating the filter based on a preset LMS algorithm by using the clean noise information and the last-minute residual noise information includes:
obtaining calculated sound transmission information according to the external noise collected by the reference microphone through the estimation feedforward path;
and updating the filter based on a preset LMS algorithm by utilizing the calculated acoustic information and the last-moment residual noise information.
A second aspect of the present invention provides an active noise reduction apparatus for a speech device, the speech device comprising: the active noise reduction device of the voice equipment comprises an error microphone, a reference microphone, a filter and a loudspeaker, wherein the active noise reduction device of the voice equipment comprises:
the acquisition module is used for acquiring external noise information, noise information acquired by the reference microphone and last-moment residual noise information acquired by the error microphone;
the compensation module is used for compensating the noise information to obtain clean noise information;
the updating module is used for updating the filter based on a preset LMS algorithm by utilizing the clean noise information and the last-moment residual noise information;
the noise reduction module is used for receiving the clean noise information according to the updated filter, and the loudspeaker correspondingly plays the noise reduction information;
and the offset module is used for offsetting according to the noise reduction information and the external noise information to obtain new residual noise information, and returning and re-executing the steps.
A third aspect of the present invention provides an active noise reduction device for a speech device, the active noise reduction device comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the device to perform an active noise reduction method of the speech device as in any one of the above.
A fourth aspect of the present invention provides a computer-readable storage medium of a speech device, the computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to execute the active noise reduction method of the speech device.
In the technical scheme provided by the invention, the obtained noise information and the last-moment noise reduction information are counteracted to obtain clean noise information, the clean noise information and the obtained last-moment residual noise information are utilized to update the filter based on a preset LMS algorithm, the updated filter receives the clean noise information according to the clean noise information, the loudspeaker correspondingly plays the noise reduction information, the noise reduction information and the external noise information are counteracted to obtain new residual noise information, the steps are returned and re-executed to continuously update the residual noise information until the residual noise information approaches zero to obtain clean voice information, and the problem that the noise in the voice cannot be effectively removed by the existing equipment is solved.
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FIG. 1 is a schematic diagram of a first embodiment of an active noise reduction method for a speech device according to an embodiment of the present invention;
FIG. 2 is a diagram of a second embodiment of an active noise reduction method for a speech device according to an embodiment of the present invention;
FIG. 3 is a diagram of a third embodiment of an active noise reduction method of a speech device according to an embodiment of the present invention;
FIG. 4 is a diagram of a fourth embodiment of an active noise reduction method for a speech device according to an embodiment of the present invention;
FIG. 5 is a diagram of a fifth embodiment of an active noise reduction method of a speech device according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an embodiment of an active noise reduction apparatus of a speech device according to an embodiment of the present invention;
fig. 7 is a schematic diagram of an embodiment of an active noise reduction device of a speech device in an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides an active noise reduction method, an active noise reduction system, an active noise reduction device, active noise reduction equipment and a storage medium of voice equipment.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For understanding, a detailed flow of an embodiment of the present invention is described below, with reference to fig. 1 to 5, an embodiment of an active noise reduction method for a speech device in an embodiment of the present invention includes: the active noise reduction method of the voice equipment comprises the following steps:
101. acquiring external noise information, noise information acquired by the reference microphone and last-moment residual noise information acquired by the error microphone;
in this embodiment, the external noise information is obtained by transmitting external noise through an acoustic path, and the noise information includes the noise reduction information and the external noise that are respectively collected by the reference microphone and played by the speaker, where the external noise is transmitted in the form of sound wave and then is received by the reference microphone and then is converted into computer-readable external noise data,
For the last moment feedback data passing through the estimated feedforward path and the estimated feedback path, respectively, by
Wherein the content of the first and second substances,in order to obtain the noise data of the last moment,for de-noising data, in particular。
Before 101, it is also necessary to perform:
100. and performing off-line estimation to obtain a coefficient of a preset estimation feedforward path and a coefficient of a preset estimation feedback path.
Further, the speech device further includes a white noise generator, the white noise generator is configured to play white noise information, and step 100 may further specifically execute:
1001. receiving the white noise information according to the reference microphone to obtain first white noise information, obtaining second white noise information through a preset estimation feedback path according to the white noise information, and mutually offsetting the first white noise information and the second white noise information to obtain a first difference value;
1002. receiving the white noise information according to the error microphone to obtain third white noise information, respectively obtaining fourth white noise information through a preset estimation feedforward path according to the white noise information, and mutually offsetting the third white noise information and the fourth white noise information to obtain a second difference value;
in the 1001-1002 step, since the coefficients of the noise passing through the feedforward path and the feedback path are unknown, the acoustic path coefficient P and the feedforward path coefficient need to be preset in advanceAnd feedback path coefficientsAnd performing simulation in SIMULINK to perform the first round of various data calculation and acquisition, wherein the white noise generator plays white noise set asBy white noiseRespectively passing through the feedback path, the estimated feedback path, the feedforward path and the estimated feedforward path to obtain corresponding first white noise dataSecond white noise dataThird white noise dataAnd fourth white noise data
1003. And processing the first difference value and the second difference value based on the LMS algorithm to respectively obtain a coefficient of a preset estimation feedback path and a coefficient of a preset estimation feedforward path.
In step 1003, setting is performedAsThe step size of (a) is determined,asSo that the corresponding weights are obtained respectively in the following two ways to updateCoefficient sumCoefficient:
wherein whenIn the very approach to F, the frequency of the rf,andequal; when in useAs it approaches very closely to S,andare equal.
In the first round of evaluation, since no noise passed inside, it was evaluated that、、Andare all made of
0, the reference microphone collects external noise data for the first timeWhile, no other noise is collected, so the intermediate noise data entering the estimated pathWithout superimposing other noise data therein and cancelling othersNoise data at once, thus obtaining initial sound transmission dataInitial acoustic dataDirectly through the estimated feed-forward pathObtain an initial
Calculating transaudient dataThe external noise is passed through an acoustic path P to obtain initial noise dataSince the speaker is not capable of playing and generating noise data in the initial stateCounterbalanced noise reduction data, thusBased on LMS algorithm pairAndcalculating to obtain initial estimated acoustic path coefficient:
Since the last moment of the initial estimated acoustic path coefficients is not present, the initial calculation formula is。
The error microphone receives the initial last noise data to obtain initial noise reduction data, and transmits the initial noise reduction data to the loudspeaker for playing to the outside, wherein it needs to be noted that the initial noise reduction played to the outside by the loudspeaker and the second external noise pass through the acoustic pathCarrying out the offset:deriving whether the noise reduction sound played by the speaker is the next external noise
102. compensating the noise information to obtain clean noise information;
further, step 102 may specifically further perform:
1021. obtaining last-moment noise reduction information transmitted by the estimation feedback path;
1022. and compensating the noise information according to the noise reduction information at the last moment, and offsetting the noise reduction information in the noise information.
In step 1021-The noise data of the last moment is received by the error microphone and is acquired by the reference microphone when being played by the loudspeaker, so that the feedback data is not played, and the intermediate noise data is obtained by overlapping the feedback data with the external noise dataThe concrete formula isAnd then the data needs to be counteracted by the feedback data of the last moment to leave the external noise data without impurities, namely the sound transmission data, and the specific formula is。
103. Updating the filter based on a preset LMS algorithm by using the clean noise information and the last-moment residual noise information;
further, step 103 may specifically further perform:
1031. obtaining calculated sound transmission information according to the external noise collected by the reference microphone through the estimation feedforward path;
in this embodiment, the concrete formula for obtaining the acoustic data isDetails of filter updating
Is given by the formulaWherein, in the step (A),is the filter coefficient of the last moment,in order to be the step size,
1032. And updating the filter based on a preset LMS algorithm by utilizing the calculated acoustic information and the last-moment residual noise information.
104. Receiving the clean noise information according to the updated filter, and correspondingly playing noise reduction information by the loudspeaker;
in this embodiment, after the filter receives clean noise information, a noise reduction signal is correspondingly sent out, after the speaker receives the noise reduction signal, noise reduction information with a vibration frequency opposite to that of external noise information is correspondingly played, because the propagation of sound is omnidirectional, the reference microphone also collects the noise reduction information while collecting external noise, and the noise reduction information is not needed for updating the filter internally, and even influences that the noise reduction signal transmitted after updating the filter cannot achieve an expected noise reduction effect, so that the received noise reduction information needs to be cancelled separately, and therefore, when the noise reduction signal is transmitted, the noise reduction signal passes through a preset estimation feedforward path and is transmitted to obtain the last noise reduction information for being cancelled with the noise reduction information.
105. Offsetting according to the noise reduction information and the external noise information to obtain new residual noise information, returning and re-executing the steps
In step 101-105, the new residual noise information obtained is actually obtained by performing a round of updating on the previous noise data, canceling the new round of received external noise data and obtaining new residual noise data, where the new previous noise data is received by the error microphone, and the specific formula is as followsAnd go through the winnowThe acoustic device plays and offsets the newly received noise data, and the specific formula is as follows:wherein, in the process,for a new round of external noise
The noise reduction step is repeated continuously, and updated, if the new residual noise information obtained correspondingly approaches to zero, the complete noise reduction effect can be achieved, because the residual noise data is to be transmitted to human ears, the actual equipment can interfere the noise reduction effect more or less due to the conversion between electric signals and external uncontrollable factors, the ideal state can not be achieved when the residual noise information is equal to zero in the dynamic noise reduction, therefore, a noise threshold value needs to be preset in advance, the obtained residual noise data is compared and judged with the noise threshold value, if the residual noise data is greater than the preset noise threshold value, the acoustic transmission data and the residual noise data are obtained again, the noise reduction data is updated, the new residual noise data is further obtained, whether the residual noise data is greater than the noise threshold value is judged, and the steps are repeated until the residual noise data is not greater than the noise threshold value, and then, confirming that the noise reduction is successful, outputting the audio information after the noise reduction, calculating the readable data obtained by picking up the external noise and picking up and converting the external noise according to the LMS algorithm, and obtaining a corresponding path coefficient, wherein the loudspeaker generates and plays an electric signal opposite to the path coefficient according to the corresponding path coefficient so as to offset the external noise, thereby achieving the noise reduction effect and further realizing the purpose of picking up clean user audio information.
In practical application, the music information or audio information is also received by the reference microphone and the error microphone, if the music information or audio information received by the reference microphone is not eliminated, the music information or audio information can be used as another noise information disturbing the noise reduction effect, therefore, the music information or audio information also needs to pass through an estimation feedforward path and an estimation feedback path, and the obtained estimated music information or estimated audio information is used for offsetting the music information or audio information received by the reference microphone and the error microphone next time, the residual noise information needs to be extracted into an LMS algorithm to be calculated to obtain a W coefficient approaching to P, the music information or audio information played by a loudspeaker also exists in the residual noise information, the calculation of the W coefficient can be influenced, therefore, an estimation feedforward path is arranged in advance in a circuit to transmit the music information or audio information, for canceling out music information or audio information in the residual noise information to ensure that the music information or audio information does not affect the update of W and to ensure that the user can receive clean music information or audio information.
With reference to fig. 6, the active noise reduction method of the speech device in the embodiment of the present invention is described above, and an active noise reduction apparatus of the speech device in the embodiment of the present invention is described below, where an embodiment of the active noise reduction apparatus of the speech device in the embodiment of the present invention includes:
an obtaining module 201, configured to obtain external noise information, noise information acquired by the reference microphone, and last-time residual noise information acquired by the error microphone;
the compensation module 202 is configured to compensate the noise information to obtain clean noise information;
an updating module 203, configured to update the filter based on a preset LMS algorithm by using the clean noise information and the last-moment residual noise information;
a noise reduction module 204, configured to receive the clean noise information according to the updated filter, where the speaker correspondingly plays noise reduction information;
and the counteracting module 205 is configured to counteract the noise reduction information and the external noise information to obtain new residual noise information, and return to and re-execute the above steps.
In another embodiment of the active noise reduction apparatus of a speech device in the embodiments of the present invention, the active noise reduction apparatus of a speech device includes:
an obtaining module 201, configured to obtain external noise information, noise information acquired by the reference microphone, and last-time residual noise information acquired by the error microphone;
the compensation module 202 is configured to compensate the noise information to obtain clean noise information;
an updating module 203, configured to update the filter based on a preset LMS algorithm by using the clean noise information and the last-moment residual noise information;
a noise reduction module 204, configured to receive the clean noise information according to the updated filter, where the speaker correspondingly plays noise reduction information;
and the counteracting module 205 is configured to counteract the noise reduction information and the external noise information to obtain new residual noise information, and return to and re-execute the above steps.
The active noise reduction apparatus of the speech device further includes a coefficient presetting module 200, where the coefficient presetting module 200 is specifically configured to:
and performing off-line estimation to obtain a coefficient of a preset estimation feedforward path and a coefficient of a preset estimation feedback path.
Further, the coefficient presetting module 200 may further perform:
receiving the white noise information according to the reference microphone to obtain first white noise information, obtaining second white noise information through a preset estimation feedback path according to the white noise information, and mutually offsetting the first white noise information and the second white noise information to obtain a first difference value;
receiving the white noise information according to the error microphone to obtain third white noise information, respectively obtaining fourth white noise information through a preset estimation feedforward path according to the white noise information, and mutually offsetting the third white noise information and the fourth white noise information to obtain a second difference value;
and processing the first difference value and the second difference value based on the LMS algorithm to respectively obtain a coefficient of a preset estimation feedback path and a coefficient of a preset estimation feedforward path.
The compensation module 202 may further specifically perform:
obtaining last-moment noise reduction information transmitted by the estimation feedback path;
and compensating the noise information according to the noise reduction information at the last moment, and offsetting the noise reduction information in the noise information.
The updating module 203 may further specifically execute:
obtaining calculated sound transmission information according to the external noise collected by the reference microphone through the estimation feedforward path;
and updating the filter based on a preset LMS algorithm by utilizing the calculated acoustic information and the last-moment residual noise information.
Fig. 6 above describes in detail the active noise reduction apparatus of the speech device in the embodiment of the present invention from the perspective of the modular functional entity, and the active noise reduction device in the embodiment of the present invention is described in detail below from the perspective of hardware processing.
Fig. 7 is a schematic structural diagram of an active noise reduction device of a speech device according to an embodiment of the present invention, where the active noise reduction device 300 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 310 (e.g., one or more processors) and a memory 320, and one or more storage media 330 (e.g., one or more mass storage devices) storing applications 333 or data 332. Memory 320 and storage media 330 may be, among other things, transient or persistent storage. The program stored on the storage medium 330 may include one or more modules (not shown), each of which may include a series of instructions operating on the active noise reduction device 300. Still further, processor 310 may be configured to communicate with storage medium 330 to execute a series of instruction operations in storage medium 330 on active noise reduction device 300.
The voice device based active noise reduction device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input-output interfaces 360, and/or one or more operating systems 331, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the configuration of the active noise reduction device shown in FIG. 4 does not constitute a limitation of active noise reduction based devices, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored, and when the instructions are executed on a computer, the instructions cause the computer to execute the steps of the active noise reduction method and system for a speech device.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses, and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. An active noise reduction method of a voice device, wherein the voice device comprises an error microphone, a reference microphone, a filter and a loudspeaker, and the active noise reduction method of the voice device comprises the following steps:
acquiring external noise information, noise information acquired by the reference microphone and last-moment residual noise information acquired by the error microphone;
compensating the noise information to obtain clean noise information;
updating the filter based on a preset LMS algorithm by using the clean noise information and the last-moment residual noise information;
receiving the clean noise information according to the updated filter, and correspondingly playing noise reduction information by the loudspeaker;
and offsetting according to the noise reduction information and the external noise information to obtain new residual noise information, and returning and re-executing the steps of obtaining the external noise information, the noise information acquired by the reference microphone and the last residual noise information acquired by the error microphone.
2. The active noise reduction method for a speech device according to claim 1, further comprising, before obtaining the external noise information, the noise information collected by the reference microphone, and the last-minute residual noise information collected by the error microphone:
off-line estimation is performed to derive coefficients for a preset estimated feedforward path and coefficients for a preset estimated feedback path.
3. The active noise reduction method of the speech device of claim 2, wherein the speech device further comprises a white noise generator for playing white noise information, and the performing the off-line estimation to derive the coefficients of the preset estimated feedforward path and the coefficients of the preset estimated feedback path comprises:
receiving the white noise information according to the reference microphone to obtain first white noise information, obtaining second white noise information through a preset estimation feedback path according to the white noise information, and mutually offsetting the first white noise information and the second white noise information to obtain a first difference value;
receiving the white noise information according to the error microphone to obtain third white noise information, respectively obtaining fourth white noise information through a preset estimation feedforward path according to the white noise information, and mutually offsetting the third white noise information and the fourth white noise information to obtain a second difference value;
and processing the first difference value and the second difference value based on the LMS algorithm to respectively obtain a coefficient of a preset estimation feedback path and a coefficient of a preset estimation feedforward path.
4. The active noise reduction method of the speech device according to claim 3, wherein the external noise information is obtained by external noise transmitted through an acoustic path, and the noise information includes the noise reduction information and the external noise respectively collected by the reference microphone and played by the speaker.
5. The active noise reduction method of the speech device according to claim 4, wherein the compensating the noise information to obtain clean noise information comprises:
obtaining last-moment noise reduction information transmitted by the estimation feedback path;
and compensating the noise information according to the noise reduction information at the last moment, and offsetting the noise reduction information in the noise information.
6. The active noise reduction method of a speech device according to claim 5, wherein said updating the filter based on a preset LMS algorithm using the clean noise information and the last-minute residual noise information comprises:
obtaining calculated sound transmission information according to the external noise acquired by the reference microphone through the estimation feedforward path;
and updating the filter based on a preset LMS algorithm by utilizing the calculated acoustic information and the last-moment residual noise information.
7. An active noise reduction apparatus of a speech device, the speech device comprising: the active noise reduction device of the voice equipment comprises an error microphone, a reference microphone, a filter and a loudspeaker, wherein the active noise reduction device of the voice equipment comprises:
the acquisition module is used for acquiring external noise information, noise information acquired by the reference microphone and last-moment residual noise information acquired by the error microphone;
the compensation module is used for compensating the noise information to obtain clean noise information;
the updating module is used for updating the filter based on a preset LMS algorithm by utilizing the clean noise information and the last-moment residual noise information;
the noise reduction module is used for receiving the clean noise information according to the updated filter, and the loudspeaker correspondingly plays the noise reduction information;
and the offset module is used for offsetting according to the noise reduction information and the external noise information to obtain new residual noise information, and returning and re-executing the steps.
8. An active noise reduction device of a speech device, comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the active noise reduction device to perform an active noise reduction method for a speech device of any of claims 1-6.
9. A computer-readable storage medium of a speech device, the computer-readable storage medium of the speech device having a computer program stored thereon, the speech device comprising: error microphone and loudspeaker, which computer programs, when executed by a processor, implement an active noise reduction method for a speech device according to any of claims 1-6.
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