Dual-channel high-precision pickup method and pickup device

Abstract

The invention provides a dual-channel high-precision pickup method and pickup equipment, and relates to the technical field of pickup processing. The method comprises the following steps: acquiring dual-channel sound data, and performing matching analysis based on the same source to determine homologous channel data; distortion calibration based on channel asynchronism is carried out on the homologous channel data, real supplementary processing is carried out on the calibration position, and non-distortion homologous channel data is formed; and performing source energy collaborative analysis on the non-distorted homologous channel data to obtain dual-channel pickup data. According to the method, distortion supplementation and energy collaboration based on the same sound source are carried out on the sound data collected by the two channels, so that the obtained homologous sound data are more accurate, and the reduction effect is better.

Description

Technical Field

[0001] The present invention relates to the technical field of sound pickup processing, and more particularly, to a dual-channel high-precision sound pickup method and a sound pickup device. Background Art

[0002] Dual-channel sound pickup is a way to achieve stereo sound. Compared with single-channel sound pickup, the sound pickup effect is better. Currently, there are already good processing methods for the sound data collected on the channel, including Fourier transform processing and noise reduction for the sound source, which greatly improves the collection effect of different sound source data in a single channel. However, due to the limitations of the sound data collected on a single channel itself, it is impossible to greatly optimize the sound data through subsequent reasonable processing. Therefore, the application of a single channel also has limitations.

[0003] Dual-channel sound pickup collects sound data by setting two receiving channels at an angle, and then performs complementary analysis to obtain better sound data compared with single-channel sound pickup. Currently, if the analysis and processing of the sound data collected using dual channels cannot fully achieve obvious processing effects, there is still room for improvement in distortion compensation and restoration.

[0004] Therefore, designing a dual-channel high-precision sound pickup method and a sound pickup device, through distortion compensation and energy coordination based on the same sound source for the sound data collected by dual channels, making the obtained sound data of the same source more accurate and achieving a better restoration effect, is an urgent problem to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to provide a dual-channel high-precision sound pickup method. By obtaining the sound data collected by dual channels respectively and matching them for the same sound source, and then comparing and analyzing the sound data of the same sound source on the corresponding different channels, mutual information distortion calibration and compensation are realized, further improving the information integrity of the dual-channel sound data. At the same time, reasonable amplitude energy coordination is carried out on the sound data information. In this way, not only is the lower distortion of the data guaranteed in terms of the integrity of the sound data, but also the sound energy information of the sound source can be reasonably restored, further improving the accuracy of the collected sound data, making the obtained sound data have high precision, and effectively improving the quality of dual-channel sound pickup.

[0006] The purpose of the present invention is also to provide a dual-channel high-precision sound pickup device. This system realizes the comparative analysis based on the same-source data by configuring dual channels capable of respectively collecting sound data, and then highly restores the sound information while reducing the distortion of the sound data. It effectively ensures the accuracy and precision of the collected sound data and is an important material basis for ensuring the quality of dual-channel sound pickup.

[0007] In a first aspect, the present invention provides a dual-channel high-precision sound pickup method, including: obtaining dual-channel sound data, and performing matching analysis based on the same source to determine homologous channel data; performing distortion calibration on the homologous channel data based on channel asynchrony, and performing real supplement processing on the calibrated positions to form non-distorted homologous channel data; performing source energy collaborative analysis on the non-distorted homologous channel data to obtain dual-channel sound pickup data.

[0008] In the present invention, the method performs matching correspondence of the same sound source by obtaining the sound data collected by the dual channels, and then compares and analyzes the sound data of the same sound source on the corresponding different channels to achieve mutual information distortion calibration and supplementation, further improving the information integrity of the dual-channel sound data. At the same time, reasonable amplitude energy collaboration is performed on the sound data information, so that not only the lower distortion of the data is guaranteed in terms of the integrity of the sound data, but also the sound energy information of the sound source can be reasonably restored, further improving the accuracy of the collected sound data, making the obtained sound data have a high precision, and effectively improving the quality of dual-channel sound pickup.

[0009] As a possible implementation, obtaining dual-channel sound data, and performing matching analysis based on the same source to determine homologous channel data includes: respectively extracting the time-domain variation data of different sounds collected on the two channels to form first-channel sound data and second-channel sound data; respectively extracting the first time-domain variation function of different sounds in the first-channel sound data and the second time-domain variation function of different sounds in the second-channel sound data , where m is the number of different first time-domain variation functions in the first-channel sound data, and n is the number of different second time-domain variation functions in the second-channel sound data; performing matching analysis in the time dimension on the first time-domain variation function and the second time-domain variation function to determine the homologous first time-domain variation function and second time-domain variation function, and respectively calibrating them as the homologous first matching variation function and the homologous second matching variation function , where k is the number of determined different matching sounds.

[0010] In the present invention, the sound data collected by two channels are processed reasonably to form the sound data of different sound sources. Since the sound data collected by the two channels are different due to the differences in the collection directions of the channels and the distances from the relative sound sources, it is impossible to quickly correspond the sound data collected on the two channels for the same sound source, but reasonable analysis is required to determine. It should be noted here that, first, the method of extracting the sound data of the corresponding sound source by extracting the sound data of different sound sources from the sound data collected on the channel is diverse, such as Fourier transform analysis, amplitude-based feature analysis, etc. Second, for the matching and corresponding of the sound data of the same sound source on different channels, to ensure the accuracy and reasonableness of the matching analysis, the expression of the sound data needs to be consistent. Considering the simplicity of data analysis in this application, the sound data are all expressed in the form of a function in the time domain to achieve reasonable processing in the time domain during the matching analysis.

[0011] As a possible implementation, perform matching analysis on the first time-domain variation function and the second time-domain variation function in the time dimension to determine the first time-domain variation function and the second time-domain variation function of the same source, and label them as the first homologous matching variation function and the second homologous matching variation function respectively, including: for any first time-domain variation function , if there exists a time displacement amount ∆t such that is satisfied with any second time-domain variation function throughout the entire information duration throughout the entire information duration under the following conditions, then determine that the first time-domain variation function and the second time-domain variation function for the analysis are the data collected from different channels of the same sound source: , , represents the total duration of extracting the satisfied condition, P is the matching difference threshold, represents the minimum matching duration ratio, represents taking and the smaller value; label the first time-domain variation function that meets the matching condition as the first homologous matching variation function , and label the second time-domain variation function that meets the matching condition as the second homologous matching variation function .

[0012] In the present invention, for the matching analysis method of the sound data of the same sound source on two channels, it is considered that the difference in the homologous sound data of the two channels in the time domain is mainly caused by the position difference of the channels relative to the sound source. Therefore, when performing the matching analysis, it is considered that the channel with a longer distance will have a lag compared to the channel with a shorter distance when receiving the same information. Therefore, the matching judgment basis of the homologous sound data can be obtained through the time translation transformation of the time domain function. Of course, it is considered that there will still be a certain deviation in the originally acquired sound data even after the time translation transformation, because the acquisition and processing do not completely eliminate defects such as distortion and noise. However, as long as the gap between the two is within the allowable range, the homologous sound data that match each other on the two channels can be accurately judged. Here, the threshold for the analysis and judgment includes two aspects. On the one hand, the difference in amplitude at the mutually matching time positions needs to be within the allowable threshold range. On the other hand, the total duration ratio of the deviation cannot exceed the limited ratio. The matching difference threshold and the minimum matching duration ratio can be set according to the actual situation or determined based on big data analysis.

[0013] As a possible implementation method, distortion calibration based on channel asynchrony is performed on the homologous channel data, and real supplementation processing is performed on the calibrated positions to form non-distorted homologous channel data, including: for the homologous first matching change function and the homologous second matching change function , extract the information on the time periods that do not satisfy in the matching analysis, and respectively form the homologous first non-adaptive segment function and the homologous second non-adaptive segment function , where i represents the numbers of multiple different consecutive time periods that do not satisfy ; perform calibration analysis of frequency distortion on the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function to form the distortion period data corresponding to the same sound source; perform real supplementation processing on the distortion period data corresponding to the matching change function to form non-distorted homologous channel data.

[0014] In the present invention, after determining the sound data of the same sound source on different channels, the two sound data can be used for comparative analysis to determine the distortion caused by the performance of channel data acquisition, and then reasonable supplementation can be carried out for the distorted part to improve the quality of sound data. It can be understood that if two matching sound time-domain variation functions have different degrees of distortion, the difference between the two sound time-domain variation functions during the distorted time period is relatively large, exceeding the allowable matching deviation range. Therefore, the distorted part must belong to the time period when the amplitude difference exceeds the allowable deviation threshold. Of course, the time period when the amplitude difference exceeds the allowable threshold does not necessarily correspond one-to-one to the distorted time period. After all, data acquisition is also affected by the environment, etc. Therefore, reasonable analysis and judgment are required to accurately determine the time period of data distortion.

[0015] As a possible implementation, for the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function perform calibration analysis of frequency distortion to form distortion time period data corresponding to the same sound source, including: for the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function , if the following conditions are met, the corresponding time period is determined as the distorted time period: there exists a time scaling factor x such that ; extract the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function within the time period determined as the distorted time period to form distortion time period data.

[0016] In the present invention, the determination of the time period of data distortion mainly considers that distortion will cause frequency changes, and thus mutual correspondence cannot be carried out. For the frequency correspondence analysis and judgment in the time-domain function, it is mainly determined by performing scaling analysis in the time domain of the function. Of course, due to the influence of environmental factors, there is also a certain deviation in the matching comparison after scaling, but if this deviation is within the allowable threshold range, then the corresponding matching time period can be accurately determined as the distorted time period.

[0017] As a possible implementation, perform real supplementation processing of the distortion on the distortion time period data corresponding to the matching change function to form non-distorted homologous channel data, including: for different distorted time periods, determine the homologous first pre-frequency value before and after the time period of the homologous first non-adaptive segment function and the homologous first post-frequency value as well as the homologous first average frequency value of the homologous first non-adaptive segment function ; for different distorted time periods, determine the homologous second non-adaptive segment function The homologous second pre-frequency value before and after the time period and the homologous second post-frequency value as well as the homologous second non-adaptive segment function of the homologous second average frequency value ; for the corresponding matching change function, according to the homologous first non-adaptive segment function the corresponding homologous first pre-frequency value the homologous first post-frequency value as well as the homologous first average frequency value and the homologous second non-adaptive segment function the corresponding homologous second pre-frequency value the homologous second post-frequency value as well as the homologous second average frequency value perform distortion compensation processing to form non-distorted homologous channel data.

[0018] In the present invention, the main consideration for supplementing the distorted part of the sound data is that the distortion causes frequency changes. Therefore, two homologous sound data are used for mutual comparison and supplementation to better restore the distorted part. Here, the most important thing for distortion compensation is to determine which of the two sound data is distorted and needs to be supplemented. Normally, for the obtained sound, especially the frequency change of the human voice, it is regular and there will be no sudden frequency fluctuations. Therefore, it can be determined by comparing and analyzing the frequency values before and after the distorted segment with the average frequency value of the distorted segment.

[0019] As a possible implementation, for the corresponding matching change function, according to the homologous first non-adaptive segment function the corresponding homologous first pre-frequency value the homologous first post-frequency value as well as the homologous first average frequency value and the homologous second non-adaptive segment function the corresponding homologous second pre-frequency value the homologous second post-frequency value as well as the homologous second average frequency value perform distortion compensation processing to form non-distorted homologous channel data, including: if for the homologous first non-adaptive segment function satisfies: for the homologous second non-adaptive segment function does not satisfy: then, on the premise of ensuring that the average amplitude of the homologous second non-adaptive segment function remains unchanged during the distorted time period, assign the frequency of the homologous first non-adaptive segment function during the distorted time period to the homologous second non-adaptive segment function ; If for the homologous first non - adaptive segment function , the following is not satisfied: , and for the homologous second non - adaptive segment function , the following is satisfied: , then while ensuring that the average amplitude of the homologous first non - adaptive segment function remains unchanged during the distortion period, assign the frequency of the homologous second non - adaptive segment function during the distortion period to the homologous first non - adaptive segment function ; If for the homologous first non - adaptive segment function , the following is satisfied: , and for the homologous second non - adaptive segment function , the following is satisfied: , then determine the frequency offset of the homologous first non - adaptive segment function and the frequency offset of the homologous second non - adaptive segment function . When , then while ensuring that the average amplitude of the homologous second non - adaptive segment function remains unchanged during the distortion period, assign the frequency of the homologous first non - adaptive segment function during the distortion period to the homologous second non - adaptive segment function . When , then while ensuring that the average amplitude of the homologous first non - adaptive segment function remains unchanged during the distortion period, assign the frequency of the homologous second non - adaptive segment function during the distortion period to the homologous first non - adaptive segment function . When , then and assign the frequency value of the homologous non - adaptive segment function corresponding to the larger value to and corresponding to the smaller value of the homologous non - adaptive segment function while ensuring the average amplitude remains unchanged. Among them, , ; If for the homologous first non - adaptive segment function , the following is not satisfied: , and for the homologous second non - adaptive segment function , the following is not satisfied: , then determine the frequency offset of the homologous first non - adaptive segment function and the frequency offset of the homologous second non - adaptive segment function . When , then while ensuring that the average amplitude of the homologous second non - adaptive segment function remains unchanged during the distortion period, assign the frequency of the homologous first non - adaptive segment function Assign the frequency on the distortion period to the homologous second non-adaptive segment function When While ensuring that the average amplitude of the homologous first non-adaptive segment function remains unchanged during the distortion period, assign the frequency of the homologous second non-adaptive segment function on the distortion period to the homologous first non-adaptive segment function When then and assign the frequency value of the homologous non-adaptive segment function corresponding to the larger value in and to the homologous non-adaptive segment function corresponding to the smaller value in and ensure that the average amplitude remains unchanged; after performing distortion compensation processing on all distortion periods of the corresponding matching change function, form non-distorted homologous channel data.

[0020] In the present invention, when using the frequency values at the time points before and after the distortion segment and the average frequency value of the distortion segment to perform comparative analysis of the distortion, the following three situations will occur. One is that the average frequency of the corresponding distortion periods on two sound data does not satisfy the sequential change. In this case, perform frequency adjustment with the average amplitude unchanged during the distortion period on the sound data that does not satisfy, and keep the frequency consistent with the frequency of the sound data that satisfies the condition. It should be noted that for the situation of frequency sequential change in this application, it mainly judges the situation where the frequency value from the previous frequency to the subsequent frequency increases from small to large. According to the actual situation, there may also be a situation where it decreases from large to small, as long as the three frequency values satisfy sequential change. The third situation is that both sound data satisfy the sequential change. At this time, it is determined according to the difference between the average frequency value relative to the previous frequency value and the subsequent frequency value respectively. Perform frequency change with the average amplitude unchanged on the sound data with a larger difference to be the same as the frequency change of the sound data with a smaller difference. If the differences are equal, use the size of the average value as the basis, and assign the frequency information with a larger average frequency value to the sound data with a smaller average frequency value. The third is that both sound data do not satisfy the sequential change. Similarly, it is also necessary to judge the difference between the previous frequency value and the subsequent frequency value to determine the object of distortion compensation. Here, when the differences are equal, the one with a smaller average frequency value is used as the compensation object because it is considered that the data with a larger frequency is more effective. After all, when the sound data is received in the channel, it has already propagated in the environment and is affected by the environment, resulting in possible attenuation of the frequency, and the data with a larger frequency is relatively less affected by the environment.

[0021] As a possible implementation method, perform source energy collaborative analysis on the non-distorted homologous channel data to obtain dual-channel pick-up data, including: obtaining the theoretical unit amplitude attenuation of the dual channels and the effective channel spacing ; For the homologous first matching change functions corresponding to each other after distortion compensation processing and the homologous second matching change functions , combined with the theoretical unit amplitude attenuation and the effective channel spacing , perform energy collaborative analysis to obtain dual-channel pick-up data.

[0022] In the present invention, after distortion compensation is completed, the amplitudes of the two homologous sound data formed will change after reception due to the distance between the acquisition channels and the sound source. Therefore, energy collaboration is required to avoid the influence of the environment on the sound energy information and affect the quality of pick-up. Here, for energy collaboration, the main consideration is the gap between the theoretical attenuation and the actual attenuation result of energy, and collaborative processing is performed according to the gap.

[0023] As a possible implementation manner, for the homologous first matching change functions corresponding to each other after distortion compensation processing and the homologous second matching change functions , combined with the theoretical unit amplitude attenuation and the effective channel spacing , perform energy collaborative analysis to obtain dual-channel pick-up data, including: determining the actual amplitude attenuation change rate according to the homologous first matching change functions corresponding to each other after distortion compensation , the homologous second matching change functions , and the effective channel spacing , where: ; According to the actual amplitude attenuation change rate and the theoretical unit amplitude attenuation , perform the following energy collaborative analysis: If , then the homologous first matching change functions corresponding to each other after distortion compensation and the homologous second matching change functions remain unchanged; If , then determine time period and the corresponding excess amount, and perform cancellation and compensation according to the ratio of the amplitude size on the homologous first matching change function to the corresponding amplitude size on the homologous second matching change function for the excess amount, so that the corresponding time period satisfies ; Determine the corresponding homologous first matching change function and the homologous second matching change function after energy collaborative analysis is completed as the pick-up information of the same sound source.

[0024] In the present invention, collaborative analysis mainly compares whether the unit attenuation formed by the energy difference between two voice data relative to the distance between two channels is collaborative with the theoretical unit attenuation. If it is within the allowable threshold range, it is determined to be collaborative and no collaboration is required, that is, the influence of the environment on the amplitude is consistent and will not reduce the quality of sound pickup. If it exceeds the threshold range, it is considered that the environment has an effect, and it is necessary to reasonably increase or decrease according to the relative amount of the amplitudes received by the two channels to ensure that the difference is adjusted within the allowable threshold range.

[0025] In a second aspect, the present invention provides a dual-channel high-precision sound pickup device, including: a first-channel acquisition unit for acquiring voice data to form first-channel voice data; a second-channel acquisition unit for acquiring voice data to form second-channel voice data; a distortion collaborative analysis unit for performing distortion calibration and supplementation on the first-channel voice data acquired by the first-channel acquisition unit and the second-channel voice data acquired by the second-channel acquisition unit, and performing energy collaborative analysis to form dual-channel sound pickup data; a result output unit for acquiring the dual-channel sound pickup data acquired by the distortion collaborative analysis unit and outputting it; an acquisition control unit for controlling the acquisition of voice data by the first-channel acquisition unit and the second-channel acquisition unit, and adjusting the acquisition angles of the first-channel acquisition unit and the second-channel acquisition unit; a ranging unit for performing human activity detection and controlling the operation of the acquisition control unit according to the monitoring results.

[0026] In the present invention, the system realizes a comparison analysis based on the same sound source data through a dual-channel configured to separately acquire voice data, and then highly restores the organic whole of the voice information in the case of reducing voice data distortion, effectively ensuring the accuracy and precision of the acquired voice data, which is an important material basis for ensuring the quality of dual-channel sound pickup. At the same time, the ranging unit measures whether there is human activity within the measurement range to control the acquisition operation, which can effectively avoid empty acquisition and save resources.

[0027] The beneficial effects of a dual-channel high-precision sound pickup method and a sound pickup device provided by the present invention are as follows: This method matches and corresponds the voice data separately acquired by the dual-channel for the same sound source, and then compares and analyzes the voice data of the same sound source on the corresponding different channels to achieve mutual information distortion calibration and supplementation, further improving the information integrity of the dual-channel voice data. At the same time, reasonable amplitude energy collaboration is performed on the voice data information, which not only ensures low distortion of the data in terms of the integrity of the voice data, but also can reasonably restore the voice energy information of the sound source, further improving the accuracy of the acquired voice data, making the acquired voice data have high precision, and effectively improving the quality of dual-channel sound pickup.

[0028] The device can respectively collect sound data through two channels configured to realize comparative analysis based on the same sound source data, and then highly restore the sound information as an organic whole under the condition of reducing sound data distortion, effectively ensuring the accuracy and precision of the collected sound data, which is an important material basis for ensuring the quality of two-channel sound pickup. At the same time, the ranging unit measures whether there is human activity within the measurement range to control the acquisition operation, which can effectively avoid empty acquisition and save resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0030] Figure 1 It is a step diagram of the two-channel high-precision sound pickup method provided by the embodiment of the present invention; Figure 2 It is a structural schematic diagram of the two-channel high-precision sound pickup system provided by the embodiment of the present invention; Figure 3 It is a distortion compensation step diagram of the two-channel high-precision sound pickup method provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The following will describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention.

[0032] Two-channel sound pickup is a way to achieve stereo. Compared with single-channel, the sound pickup effect is better. Currently, there are already good processing methods for the sound data collected on the channel, including Fourier transform processing and noise reduction for the sound source, which greatly improves the acquisition effect of different sound source data in the single channel. However, due to the limitations of the sound data collected on the single channel itself, the sound data cannot be greatly optimized through subsequent reasonable processing, so the application of the single channel is also limited.

[0033] Two-channel sound pickup respectively collects sound data by setting two receiving channels at an angle, and then conducts complementary analysis to obtain better sound data compared with the single channel. Currently, if the analysis and processing of the sound data collected by the two channels cannot fully obtain obvious processing effects, there is still room for improvement in distortion compensation and restoration.

[0034] REFERENCE Figures 1 to 3, an embodiment of the present invention provides a dual-channel high-precision sound pickup method. This method matches and corresponds to the sound data collected by the two channels for the same sound source, and then compares and analyzes the sound data of the same sound source on the corresponding different channels to achieve mutual information distortion calibration and supplementation, further improving the information integrity of the dual-channel sound data. At the same time, a reasonable amplitude energy coordination is carried out on the sound data information, so that not only a low distortion of the data is ensured in terms of the integrity of the sound data, but also the sound energy information of the sound source can be reasonably restored, further improving the accuracy of the collected sound data, making the obtained sound data have a high precision, and effectively improving the quality of dual-channel sound pickup.

[0035] The dual-channel high-precision sound pickup method specifically includes the following steps: S1: Obtain dual-channel sound data and perform matching analysis based on the same source to determine homologous channel data.

[0036] Obtaining dual-channel sound data and performing matching analysis based on the same source to determine homologous channel data includes: respectively extracting the time-domain change data of different sounds collected on the two channels to form first-channel sound data and second-channel sound data; respectively extracting the first time-domain change functions of different sounds in the first-channel sound data and the second time-domain change functions of different sounds in the second-channel sound data , where m is the number of different first time-domain change functions in the first-channel sound data, and n is the number of different second time-domain change functions in the second-channel sound data; perform matching analysis on the first time-domain change function and the second time-domain change function in the time dimension to determine the homologous first time-domain change function and second time-domain change function, and respectively label them as homologous first matching change function and homologous second matching change function , where k is the number of determined different matching sounds.

[0037] After reasonable processing of the sound data collected from two channels, the sound data of different sound sources are formed. Due to the differences in the collection directions of the two channels and the distances from the relative sound sources, it is impossible to quickly correspond the sound data collected on the two channels for the same sound source, but rather reasonable analysis is required for determination. It should be noted here that, first, the methods for extracting the sound data of corresponding sound sources from the sound data collected on the channels are diverse, such as Fourier transform analysis, amplitude-based feature analysis, etc. Second, for matching and corresponding the sound data of the same sound source on different channels, to ensure the accuracy and reasonableness of the matching analysis, the expression of the sound data needs to be consistent. Considering the simplicity of data analysis in this application, the sound data are all expressed in the form of functions in the time domain to achieve reasonable processing in the time domain during the matching analysis.

[0038] For the first time-domain variation function and the second time-domain variation function perform matching analysis in the time dimension to determine the first and second time-domain variation functions of the same source, and respectively label them as the first homologous matching variation function and the second homologous matching variation function , including: for any first time-domain variation function , if there exists a time displacement amount ∆t such that over the entire information duration is satisfied with any one of the second time-domain variation functions over the entire information duration , then determine that the first time-domain variation function and the second time-domain variation function collected from different channels of the same sound source are as follows: , , represents extracting the total duration that satisfies conditions, P is the matching difference threshold, represents the minimum matching duration ratio, represents taking and the smaller value of; label the first time-domain variation function that satisfies the matching condition as the first homologous matching variation function , and label the second time-domain variation function that satisfies the matching condition as the second homologous matching variation function .

[0039] For the matching analysis method of sound data for the same sound source on two channels, it is considered that the difference in the homologous sound data of the two channels in the time domain is mainly caused by the position difference of the channels relative to the sound source. Therefore, when performing the matching analysis, it is considered that the channel farther away will have a lag compared to the closer channel when receiving the same information. So, the matching judgment basis of the homologous sound data can be carried out through the time translation transformation of the time domain function. Of course, considering that there will still be a certain deviation in the originally acquired sound data even after the time translation transformation, this is because the acquisition and processing do not completely eliminate defects such as distortion and noise. However, as long as the gap between the two is within the allowable range, the homologous sound data that match each other on the two channels can be accurately judged. Here, the threshold for analysis and judgment includes two aspects. On the one hand, the difference in amplitude at the mutually matching time positions needs to be within the allowable threshold range. On the other hand, the total duration ratio of the deviation cannot exceed the limited ratio. The matching difference threshold and the minimum matching duration ratio can be set according to the actual situation or determined based on big data analysis.

[0040] S2: Perform distortion calibration on the homologous channel data based on channel asynchrony, and perform real supplement processing on the calibrated positions to form non-distorted homologous channel data.

[0041] Perform distortion calibration on the homologous channel data based on channel asynchrony, and perform real supplement processing on the calibrated positions to form non-distorted homologous channel data, including: for the homologous first matching change function and the homologous second matching change function , extract the information on the time periods that do not meet in the matching analysis, and respectively form the homologous first non-adaptive segment function and the homologous second non-adaptive segment function , where i represents the numbers of multiple different consecutive time periods that do not meet ; perform calibration analysis of frequency distortion on the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function to form the distortion period data corresponding to the same sound source; perform real supplement processing of the distortion on the distortion period data corresponding to the matching change function to form non-distorted homologous channel data.

[0042] After determining the sound data of the same sound source on different channels, the two sound data can be used for comparative analysis to determine the distortion caused by the performance of channel data acquisition, and then reasonable supplementation can be carried out for the distorted part to improve the quality of sound data. It can be understood that if two matching sound time-domain variation functions have different degrees of distortion, the difference between the two sound time-domain variation functions in the distorted time period is relatively large, exceeding the allowable matching deviation range. Therefore, the distorted part must be the time period where the amplitude difference exceeds the allowable deviation threshold. Of course, the time period where the amplitude difference exceeds the allowable threshold does not necessarily correspond one-to-one with the distorted time period. After all, data acquisition is also affected by the environment, etc. Therefore, reasonable analysis and judgment are needed to accurately determine the time period of data distortion.

[0043] For the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function perform calibration analysis of frequency distortion to form distortion time period data corresponding to the same sound source, including: for the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function , if the following conditions are met, then determine the corresponding time period as the distorted time period: there exists a time scaling factor x such that ; extract the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function within the time period determined to be the distorted time period to form distortion time period data.

[0044] The determination of the time period of data distortion mainly considers that distortion will cause changes in frequency, and thus mutual correspondence cannot be carried out. For the frequency correspondence analysis and judgment in the time-domain function, it is mainly determined by performing scaling analysis on the function in the time domain. Of course, due to the influence of environmental factors, there is also a certain deviation in the matching comparison after scaling, but if this deviation is within the allowable threshold range, then the corresponding matching time period can be accurately determined as the distorted time period.

[0045] Perform real supplementation processing of distortion on the distortion time period data corresponding to the matching variation function to form non-distorted homologous channel data, including: for different distortion time periods, determine the homologous first pre-frequency value before and after the time period of the homologous first non-adaptive segment function and the homologous first post-frequency value as well as the homologous first average frequency value of the homologous first non-adaptive segment function ; for different distortion time periods, determine the homologous second pre-frequency value before and after the time period of the homologous second non-adaptive segment function and the homologous second post-frequency value and a homologous second non-adaptive segment function of the homologous second average frequency value ; for the corresponding matching change function, according to the homologous first non-adaptive segment function the corresponding homologous first pre-frequency value , the homologous first post-frequency value and the homologous first average frequency value and the homologous second non-adaptive segment function the corresponding homologous second pre-frequency value , the homologous second post-frequency value and the homologous second average frequency value perform distortion compensation processing to form non-distorted homologous channel data.

[0046] Complementing the distorted part of the sound data mainly considers that the distortion causes frequency changes. Therefore, two homologous sound data are used for mutual comparison and complementation to better restore the distorted part. Here, the most important thing in performing distortion compensation is to determine which of the two sound data is distorted and needs to be compensated. Normally, for the obtained sound, especially the frequency change of the human voice, it is regular and there will be no sudden frequency fluctuations. Therefore, it can be determined by comparing and analyzing the frequency values before and after the distorted segment with the average frequency value of the distorted segment.

[0047] For the corresponding matching change function, according to the homologous first non-adaptive segment function the corresponding homologous first pre-frequency value , the homologous first post-frequency value and the homologous first average frequency value and the homologous second non-adaptive segment function the corresponding homologous second pre-frequency value , the homologous second post-frequency value and the homologous second average frequency value perform distortion compensation processing to form non-distorted homologous channel data, including: if for the homologous first non-adaptive segment function , it satisfies: , for the homologous second non-adaptive segment function , it does not satisfy: , then on the premise of ensuring that the average amplitude of the homologous second non-adaptive segment function remains unchanged during the distorted period, assign the frequency of the homologous first non-adaptive segment function during the distorted period to the homologous second non-adaptive segment function ; if for the homologous first non-adaptive segment function , it does not satisfy: , for the homologous second non-adaptive segment function , satisfying: , then, while ensuring that the average amplitude of the first non - adaptive segment function of the same source remains unchanged during the distortion period, assign the frequency of the second non - adaptive segment function of the same source during the distortion period to the first non - adaptive segment function of the same source ; If for the first non - adaptive segment function of the same source , satisfying: , and for the second non - adaptive segment function of the same source , satisfying: , then determine the frequency offset of the first non - adaptive segment function of the same source and the frequency offset of the second non - adaptive segment function of the same source , when , then, while ensuring that the average amplitude of the second non - adaptive segment function of the same source remains unchanged during the distortion period, assign the frequency of the first non - adaptive segment function of the same source during the distortion period to the second non - adaptive segment function of the same source , when , then, while ensuring that the average amplitude of the first non - adaptive segment function of the same source remains unchanged during the distortion period, assign the frequency of the second non - adaptive segment function of the same source during the distortion period to the first non - adaptive segment function of the same source , when , then and assign the frequency value corresponding to the larger value to the non - adaptive segment function of the same source corresponding to the smaller value of and while ensuring the average amplitude remains unchanged, where , ; If for the first non - adaptive segment function of the same source , not satisfying: , and for the second non - adaptive segment function of the same source , not satisfying: , then determine the frequency offset of the first non - adaptive segment function of the same source and the frequency offset of the second non - adaptive segment function of the same source , when , then, while ensuring that the average amplitude of the second non - adaptive segment function of the same source remains unchanged during the distortion period, assign the frequency of the first non - adaptive segment function of the same source during the distortion period to the second non - adaptive segment function of the same source , when , then while ensuring that the average amplitude of the first non - adaptive segment function of the same source remains unchanged during the distortion period, assign the frequency of the second non - adaptive segment function of the same source during the distortion period to the first non - adaptive segment function of the same source , when , then and assign the frequency value of the non - adaptive segment function of the same source corresponding to the larger value in and to the non - adaptive segment function of the same source corresponding to the smaller value in

[0048] while ensuring the average amplitude remains unchanged; after performing distortion compensation processing on all distortion periods of the corresponding matching change function, form non - distorted same - source channel data.

[0048] When performing comparative analysis of distortion using the frequency values at the time points before and after the distortion segment and the average frequency value of the distortion segment, the following three situations will occur. One is that the average frequency of the corresponding distortion periods on two sound data does not satisfy the sequential change. In this case, perform frequency adjustment on the sound data that does not satisfy, with the average amplitude remaining unchanged during the distortion period, and the frequency is the same as that of the sound data that satisfies the condition. It should be noted that in this application, for the situation of frequency sequential change, mainly the case where the frequency value changes from small to large from the previous frequency to the subsequent frequency is judged. According to the actual situation, there may also be a situation where it changes from large to small, as long as the three frequency values are sequentially changed. The third situation is that both sound data satisfy the sequential change. At this time, it is determined according to the difference between the average frequency value and the previous frequency value and the subsequent frequency value respectively. Perform frequency change with the average amplitude remaining unchanged on the sound data with the larger difference to be the same as the frequency change of the sound data with the smaller difference. If the differences are equal, then use the size of the average value as the basis, and assign the frequency information with the larger average frequency value to the sound data with the smaller average frequency value. The third is that both sound data do not satisfy the sequential change. Similarly, judge the size of the difference relative to the previous frequency value and the subsequent frequency value to determine the object of distortion compensation. Here, when the differences are equal, the one with the smaller average frequency value is used as the compensation object, considering that the data with a larger frequency is more effective. After all, when the sound data is received by the channel, it has propagated in the environment and may have suffered frequency attenuation due to the influence of the environment, and the data with a larger frequency is relatively less affected by the environment.

[0049] S3: Perform source energy collaborative analysis on the non - distorted same - source channel data to obtain dual - channel pick - up data.

[0050] Performing source energy collaborative analysis on the non - distorted same - source channel data to obtain dual - channel pick - up data includes: obtaining the theoretical unit amplitude attenuation of the dual channels and the effective channel spacing ; For the homologous first matching variation functions corresponding to each other after distortion compensation processing and the homologous second matching variation functions , combined with the theoretical unit amplitude attenuation and the effective channel spacing , perform energy collaborative analysis to obtain dual-channel pick-up data.

[0051] After distortion compensation is completed, the two homologous sound data formed will have their amplitudes changed after reception due to the distance between the acquisition channels and the sound source. Therefore, energy collaboration is required to avoid the influence of the environment on the authenticity of the sound energy information and affect the quality of pick-up. Here, for the energy collaboration, the main consideration is the gap between the theoretical attenuation and the actual attenuation results of the energy, and collaborative processing is carried out according to the gap.

[0052] For the homologous first matching variation functions corresponding to each other after distortion compensation processing and the homologous second matching variation functions , combined with the theoretical unit amplitude attenuation and the effective channel spacing , perform energy collaborative analysis to obtain dual-channel pick-up data, including: according to the homologous first matching variation functions corresponding to each other after distortion compensation , the homologous second matching variation functions and the effective channel spacing , determine the actual amplitude attenuation change rate , where: ; According to the actual amplitude attenuation change rate and the theoretical unit amplitude attenuation , perform the following energy collaborative analysis: If , then the homologous first matching variation functions corresponding to each other after distortion compensation and the homologous second matching variation functions remain unchanged; If , then determine time period and the corresponding excess amount, and according to the excess amount, respectively perform cancellation and compensation according to the ratio of the amplitude magnitude on the homologous first matching variation function to the corresponding amplitude magnitude on the homologous second matching variation function , so that the corresponding time period satisfies ; After completing the energy collaborative analysis, the corresponding homologous first matching variation function and the homologous second matching variation function are determined as the pick-up information of the same sound source.

[0053] Cooperative analysis mainly compares whether the unit attenuation formed by the energy difference between two voice data relative to the distance between two channels is cooperative with the theoretical unit attenuation. If it is within the allowable threshold range, it is determined to be cooperative and no cooperation is required, that is, the influence of the environment on the amplitude is consistent and will not reduce the sound pickup quality. However, if it exceeds the threshold range, it is considered that the environment has an effect, and it is necessary to reasonably increase or decrease according to the relative amount of the amplitudes received by the two channels to ensure that the difference is adjusted within the allowable threshold range.

[0054] The present invention also provides a dual-channel high-precision sound pickup device. The system includes: a first-channel acquisition unit for acquiring voice data to form first-channel voice data; a second-channel acquisition unit for acquiring voice data to form second-channel voice data; a distortion cooperative analysis unit for performing distortion calibration and supplementation on the first-channel voice data acquired by the first-channel acquisition unit and the second-channel voice data acquired by the second-channel acquisition unit, and performing energy cooperative analysis to form dual-channel sound pickup data; a result output unit for acquiring the dual-channel sound pickup data acquired by the distortion cooperative analysis unit and outputting it. The acquisition control unit is used to control the acquisition of voice data by the first-channel acquisition unit and the second-channel acquisition unit, and adjust the acquisition angles of the first-channel acquisition unit and the second-channel acquisition unit; the ranging unit is used to detect human activities and control the operation of the acquisition control unit according to the monitoring results. The ranging unit can be a laser rangefinder, which can adjust the ranging range, confirm whether there are human activities within the ranging range, and send a signal to the acquisition control unit when a person is confirmed to be present, and the acquisition control unit controls the first-channel acquisition unit and the second-channel acquisition unit to acquire voice data.

[0055] The forms of the ranging unit are diverse. In this application, it is a lidar. The laser of the lidar can sense human activities within a certain distance range. The radar detection has a large range angle. The detection angle provided in this application is 120 degrees, and the detection of the human body is intermittent and continuous detection, usually set to detect once every 3 seconds, and can be adjusted according to actual needs. When someone enters the detection range of the lidar, that is, within the set distance range of 120 degrees, the lidar triggers a human detection signal, and then controls the acquisition control unit to work according to the detection result.

[0056] It is considered that the voice data to be acquired by the acquisition control unit is human voice. Therefore, in order to ensure the timely and effective acquisition of human voice information and avoid the continuous ineffective acquisition of voice data when the lidar determines that there is no one within the detection range, the lidar controls the acquisition control unit to acquire voice data according to the detection result when detecting the human body within the detection range. That is, only when there is someone within the detection range will the acquisition control unit be controlled to acquire human voice data, but when no one is detected within the range, the acquisition control unit will be controlled to stop acquiring voice data, achieving the data acquisition control of recording when people come and stopping when people leave. On the one hand, this can ensure the effectiveness of voice data acquisition, improve the purity of the acquired data, so that the acquired voice data can be completely and effectively processed and applied without the need to judge whether there is effective voice data. On the other hand, it can also save the resources consumed by voice data acquisition to a certain extent and ensure the high utilization of resources.

[0057] The device realizes the comparative analysis based on the same sound source data and then highly restores the organic whole of the sound information in the case of reducing the distortion of the sound data by configuring two channels capable of respectively acquiring the sound data, effectively ensuring the accuracy and precision of the acquired sound data, which is an important material basis for ensuring the quality of two-channel sound pickup. At the same time, the ranging unit measures whether there is human activity within the measurement range to control the acquisition operation, which can effectively avoid empty acquisition and thus save resources.

[0058] The system provided by this application is specifically an intelligent desktop directional sound pickup device, which deeply integrates advanced sound pickup, sensing, and data transmission technologies. It internally integrates a dual-directional 8-microphone array, and cooperates with an acoustic noise reduction algorithm to filter out environmental noise and ensure the purity of the sound. The device adopts a collaborative induction trigger mechanism of laser and radar, which can sensitively and accurately capture the dynamics of the sound source. It is equipped with dual-channel voice separation, accurately distinguishes different sound-producing subjects, and locks the gain processing for the target human voice to strengthen the key sound signals. In terms of data transmission, it supports multi-mode transmission of network port, WiFi, and 4G, meeting the diverse scene requirements. Based on intelligent algorithms and sensing trigger technology in the user scenario, the device completes the one-to-one correspondence between the current work order, the target human voice, and the recording segment. It realizes high-definition sound pickup - voice separation - real-time, continuous, and complete upload of audio data to the cloud background, providing a solid foundation for applications such as data storage, analysis, and feeding models.

[0059] In summary, the beneficial effects of the two-channel high-precision sound pickup method and the sound pickup device provided by the embodiments of the present invention are as follows: This method matches and corresponds the sound data collected separately by two channels for the same sound source, and then compares and analyzes the sound data of the same sound source on the corresponding different channels to achieve mutual information distortion calibration and supplementation, further improving the information integrity of the two-channel sound data. At the same time, it reasonably coordinates the amplitude energy of the sound data information, so that not only the lower distortion of the data is guaranteed in terms of the integrity of the sound data, but also the sound energy information of the sound source can be reasonably restored, further improving the accuracy of the collected sound data, making the obtained sound data have a higher precision, and effectively improving the quality of two-channel sound pickup.

[0060] This device realizes an organic whole that highly restores sound information while reducing sound data distortion through two channels configured to collect sound data respectively for comparative analysis of data from the same sound source, effectively ensuring the accuracy and precision of the collected sound data, which is an important material basis for ensuring the quality of two-channel sound pickup. At the same time, the ranging unit measures whether there is human activity within the measurement range to control the collection operation, which can effectively avoid empty collection and thus save resources.

[0061] In the embodiments of this application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain piece of information is called the information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated. For example, but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated, etc. It is also possible to indirectly indicate the information to be indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated. It is also possible to only indicate a part of the information to be indicated, while the other parts of the information to be indicated are known or pre-agreed. For example, it is also possible to achieve the indication of specific information by relying on the arrangement order of each piece of information pre-agreed (such as protocol regulations), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can be identified and indicated uniformly to reduce the indication overhead caused by separately indicating the same information.

[0062] In addition, the specific indication method can also be various existing indication methods. For example, but not limited to, the above indication methods and their various combinations, etc. The specific details of various indication methods can refer to the prior art and will not be elaborated herein. As can be seen from the above, for example, when it is necessary to indicate multiple pieces of information of the same type, there may be a situation where the indication methods of different pieces of information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiments of this application do not limit the selected indication method. In this way, the indication methods involved in the embodiments of this application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0063] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending periods and / or sending times of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of the present application. Among them, the sending periods and / or sending times of these sub-information can be predefined, for example, predefined according to a protocol, or can be configured by the sending device by sending configuration information to the receiving device.

[0064] "Predefined" or "preconfigured" can be implemented by pre-saving corresponding codes, tables or other means that can be used to indicate relevant information in the device. The embodiments of the present application do not limit its specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately, or integrated in an encoder, decoder, processor, or communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, processor, or communication device. The type of memory can be any form of storage medium, which is not limited in the embodiments of the present application.

[0065] The "protocol" involved in the embodiments of the present application can refer to a protocol family in the communication field, a standard protocol similar to the frame structure of a protocol family, or a related protocol applied to a future communication system. The embodiments of the present application do not make specific limitations on this.

[0066] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if", and "if" all refer to that the device will perform corresponding processing under a certain objective situation, not a limited time, and it is not required that the device must have a judgment action when implemented, nor does it mean that there are other limitations.

[0067] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship. For example, A / B may represent A or B. The "and / or" in the embodiments of the present application is merely a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Also, in the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more than two. "At least one (item)" or its similar expression refers to any combination of these items, including any combination of a single item or plural items. For example, at least one (item) of a, b, or c may represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple. Additionally, for the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and terms such as "first" and "second" do not necessarily mean different. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific way for easy understanding.

[0068] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and this processor may also be other general - purpose processors, digital signal processors (DSPs), application - specific integrated circuits (ASICs), field - programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general - purpose processor may be a microprocessor or this processor may also be any conventional processor, etc.

[0069] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0071] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0072] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or a similar expression refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0073] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0074] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0075] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0076] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0077] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] In addition, the functional units in each embodiment of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0079] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0080] As described above, the above are only specific implementation manners of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A dual-channel high-precision sound pickup method, characterized in that: include: Obtain dual-channel sound data, and perform matching analysis based on the same source to determine the homologous channel data; Performing distortion calibration based on channel asynchrony on the homologous channel data, and performing true supplementary processing on the calibration position to form non-distorted homologous channel data; The non-distorted homologous channel data is subjected to source energy collaborative analysis to obtain dual-channel sound pickup data.

2. The dual-channel high-precision sound pickup method according to claim 1, characterized in that: The step of obtaining dual-channel sound data and performing matching analysis based on the same source to determine homologous channel data includes: Respectively extracting the time domain variation data of different sounds collected on the two channels to form first channel sound data and second channel sound data; Extracting first time domain variation functions of different sounds in the first channel sound data respectively and a second time domain variation function of different sounds in the second channel sound data , m is the number of different first time-domain variation functions in the first channel sound data, and n is the number of different second time-domain variation functions in the second channel sound data; The first time domain variation function and the second time domain variation function Perform matching analysis in the time dimension to determine the first time domain change function and the second time domain change function of the same source, and mark them as the first matching change function of the same source and homologous second matching change function , k is the number of different matching sounds determined.

3. The dual-channel high-precision sound pickup method according to claim 2, characterized in that: The first time domain variation function and the second time domain variation function Perform matching analysis in the time dimension to determine the first time domain change function and the second time domain change function of the same source, and mark them as the first matching change function of the same source and homologous second matching change function ,include: For any of the first time domain variation functions , if there is a time displacement ∆t such that Throughout the message length The second time domain variation function Throughout the message length If the following conditions are met, the first time domain variation function to be analyzed is determined and the second time domain variation function Collect data for different channels of the same sound source: ， ， Extraction satisfaction The total duration of the condition, P is the matching difference threshold, Indicates the minimum matching duration ratio. Indicates taking and The smaller value of ; The first time domain variation function that satisfies the matching condition Marked as the homologous first matching change function , the second time domain variation function that satisfies the matching condition Marked as the homologous second matching change function .

4. The dual-channel high-precision sound pickup method according to claim 3, characterized in that: The distortion calibration of the homologous channel data based on channel asynchrony and real supplementary processing of the calibration position to form non-distorted homologous channel data include: The first matching function of the homology and the homologous second matching change function , extract does not meet the matching analysis The information on the time period forms the homologous first non-adaptive segment function and the homologous second non-adaptive segment function , i means not satisfied The numbers of multiple different consecutive time periods; The corresponding first non-adaptive segment function of the homology and the homologous second non-adaptive segment function Conduct frequency distortion calibration analysis to generate distortion period data corresponding to the same sound source; The distorted time period data corresponding to the matching variation function is subjected to distorted true supplementation processing to form non-distorted homologous channel data.

5. The dual-channel high-precision sound pickup method according to claim 4, characterized in that: The corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function Conduct frequency distortion calibration analysis to generate distortion period data corresponding to the same sound source, including: For the corresponding homologous first non-adaptive segment function and the homologous second non-adaptive segment function , if the following conditions are met, the corresponding period is determined to be a distorted period: There exists a time scaling amount x such that ; The homologous first non-adaptive segment function corresponding to the time period of the distortion period is determined and the homologous second non-adaptive segment function Extraction forms the distortion period data.

6. The dual-channel high-precision sound pickup method according to claim 5, characterized in that: The step of performing distorted real supplementation processing on the distorted time period data corresponding to the matching variation function to form non-distorted homologous channel data includes: For different distortion periods, the homologous first non-adaptive segment function is determined The first preceding frequency value of the same source before and after the period and the first-last frequency value of the homology And the homologous first non-adaptive segment function The first average frequency of homology ; For different distortion periods, the homologous second non-adaptive segment function is determined The second preceding frequency value of the same source before and after the period and the second-last frequency value of the same source And the homologous second non-adaptive segment function The average frequency of the second homology ; For the corresponding matching change function, according to the homologous first non-adaptive segment function The corresponding first preceding frequency value of the homology , the first subsequent frequency value of the homology and the homologous first average frequency value and the homologous second non-adaptive segment function The corresponding second preceding frequency value of the homologous , the second frequency value of the same source and the homologous second average frequency value Distortion compensation processing is performed to form the non-distorted homologous channel data.

7. The dual-channel high-precision sound pickup method according to claim 6, characterized in that: The corresponding matching change function is based on the homologous first non-adaptive segment function The corresponding first preceding frequency value of the homology , the first subsequent frequency value of the homology and the homologous first average frequency value and the homologous second non-adaptive segment function The corresponding second preceding frequency value of the homologous , the second frequency value of the same source and the homologous second average frequency value Performing distortion supplementation processing to form the non-distorted homologous channel data includes: If the homologous first non-adaptive segment function ,satisfy: , for the homologous second non-adaptive segment function , does not satisfy: , then in order to ensure that the homologous second non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous first non-adaptive segment function The frequency on the distortion period is assigned to the homologous first rather than the adaptation segment function ; If the homologous first non-adaptive segment function , does not satisfy: , for the homologous second non-adaptive segment function ,satisfy: , then in order to ensure that the homologous first non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous second non-adaptive segment function The frequency on the distortion period is assigned to the homologous first non-adaptive segment function ; If the homologous first non-adaptive segment function ,satisfy: , for the homologous second non-adaptive segment function ,satisfy: , then determine the homologous first non-adaptive segment function The frequency offset and the homologous second non-adaptive segment function The frequency offset ,when , then in order to ensure that the homologous second non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous first non-adaptive segment function The frequency on the distortion period is assigned to the homologous second non-adaptive segment function ,when , then in order to ensure that the homologous first non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous second non-adaptive segment function The frequency on the distortion period is assigned to the homologous first non-adaptive segment function ,when ,but and The frequency value of the homologous non-adaptive segment function corresponding to the larger value in is assigned and The smaller value corresponds to the homologous non-adaptive segment function and ensures that the average amplitude remains unchanged, where , ; If the homologous first non-adaptive segment function , does not satisfy: , for the homologous second non-adaptive segment function , does not satisfy: , then determine the homologous first non-adaptive segment function The frequency offset and the homologous second non-adaptive segment function The frequency offset ,when , then in order to ensure that the homologous second non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous first non-adaptive segment function The frequency on the distortion period is assigned to the homologous second non-adaptive segment function ,when , then in order to ensure that the homologous first non-adaptive segment function In the case where the average amplitude remains unchanged over the distortion period, the homologous second non-adaptive segment function The frequency on the distortion period is assigned to the homologous first non-adaptive segment function ,when ,but and The frequency value of the homologous non-adaptive segment function corresponding to the larger value in is assigned and The smaller value corresponds to the homologous non-adaptive segment function and ensures that the average amplitude remains unchanged; After distortion supplementation processing is performed on all distorted time periods of the corresponding matching variation function, non-distorted homologous channel data is formed.

8. The dual-channel high-precision sound pickup method according to claim 7, characterized in that: The performing source energy collaborative analysis on the non-distorted homologous channel data to obtain dual-channel sound pickup data includes: Get the theoretical unit amplitude attenuation of dual channels and effective channel spacing ; The first matching change functions of the same source that are different from each other after the distortion supplementation processing and the homologous second matching change function , combined with the theoretical unit amplitude attenuation and the effective spacing of the channels , perform energy synergy analysis and obtain dual-channel sound pickup data.

9. The dual-channel high-precision sound pickup method according to claim 8, characterized in that: The first matching change functions of the same source that are different from each other after the distortion supplementation processing and the homologous second matching change function , combined with the theoretical unit amplitude attenuation and the effective spacing of the channels , perform energy synergy analysis and obtain dual-channel sound pickup data, including: According to the homologous first matching change functions corresponding to each other after distortion supplementation , the homologous second matching change function And the effective spacing of the channels , determine the actual amplitude attenuation change rate ,in: ； According to the actual amplitude attenuation change rate and the theoretical unit amplitude attenuation , perform the following energy synergy analysis: like , then the homologous first matching change function corresponding to each other after distortion supplementation and the homologous second matching change function constant; like , then determine The time period and the corresponding excess amount, and according to the excess amount, respectively according to the homologous first matching change function The amplitude size is matched with the homologous second variation function The corresponding amplitude is compensated to make the corresponding time period meet the ; The homologous first matching change function corresponding to the energy collaborative analysis is completed and the homologous second matching change function Determine the sound pickup information from the same sound source.

10. A dual-channel high-precision sound pickup device, characterized in that: include: A first channel acquisition unit, used for acquiring sound data to form first channel sound data; A second channel acquisition unit, used for acquiring sound data to form second channel sound data; a distortion cooperative analysis unit, configured to perform distortion calibration and supplement and energy cooperative analysis on the first channel sound data acquired by the first channel acquisition unit and the second channel sound data acquired by the second channel acquisition unit, so as to form dual-channel sound pickup data; A result output unit, used to obtain and output the dual-channel sound pickup data obtained by the distortion collaborative analysis unit; A collection control unit, used for controlling the first channel collection unit and the second channel collection unit to collect sound data, and adjusting the collection angles of the first channel collection unit and the second channel collection unit; The ranging unit is used to detect the activity and control the operation of the acquisition control unit according to the monitoring results.

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