Method, system and medium for automatically debugging audio parameters of recording channel of law enforcement instrument

Abstract

The present application provides a method, system and medium for automatically debugging the audio parameters of the recording channel of the law enforcement instrument. The method includes: obtaining the audio data of the preset time period of the law enforcement instrument, extracting the background noise data and the volume data, processing according to the background noise data, obtaining the scene category feature data, further obtaining the volume threshold, comparing with the volume data, obtaining the volume deviation rate, processing according to the working instructions of the law enforcement instrument in combination with the scene category feature data and the volume deviation rate, obtaining the audio parameters, and performing long-distance pickup or intercom, obtaining real-time environmental audio data, and extracting the audio feature data, and then adjusting the audio parameters to obtain the audio optimization parameters, and performing long-distance pickup or intercom according to the audio optimization parameters; thereby realizing the automatic calling and intelligent optimization of the audio parameters of different working instructions of the law enforcement instrument, solving the conflict problem of long-distance pickup and intercom howling of the law enforcement instrument, and improving the adaptability of the law enforcement instrument.

Description

Technical Field

[0001] The present application relates to the technical field of law enforcement recorders, and more specifically, to a method, system and medium for automatically debugging audio parameters of a recording channel of a law enforcement recorder. Background Art

[0002] As a key evidence-collecting device, the quality of the audio function of the body camera is directly related to the effectiveness of law enforcement. On the one hand, in many law enforcement actions, it is necessary to obtain clear and accurate sound information at a long distance. On the other hand, the intercom function of the body camera is crucial in close-range collaborative law enforcement. Traditional body cameras use fixed audio parameters. Due to distance attenuation, the recorded sound can easily become weak and blurred, resulting in the loss of key audio details and failing to provide strong support for subsequent case analysis. When law enforcement officers use the intercom function in close-range scenarios such as narrow spaces and indoors, they often encounter howling problems. Current body cameras have shortcomings in the application of audio parameters. Whether it is recording or intercom, most of them rely on static, single parameter settings, and cannot dynamically and intelligently switch and adapt according to actual scenarios.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of this application is to provide a method, system and medium for automatic debugging of the audio parameters of the recording channel of the law enforcement device. The method can obtain the audio parameters according to the working scenario and volume deviation rate of the law enforcement device, and optimize the parameters according to the audio feature data. The method realizes the automatic calling and intelligent optimization of the audio parameters of different working instructions of the law enforcement device, solves the conflict problem between long-distance sound pickup and intercom howling of the law enforcement device, and improves the adaptability of the law enforcement device.

[0005] This application also provides a method for automatically debugging audio parameters of a body camera recording channel, including the following steps:

[0006] Acquire the audio data of the body camera during a preset time period, extract the background noise data and volume data, process the background noise data, and obtain the scene category feature data;

[0007] Processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate;

[0008] Obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters;

[0009] Performing long-distance sound pickup or intercom according to the audio parameters, and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters;

[0010] Long-distance sound pickup or intercom is performed according to the audio optimization parameters.

[0011] Optionally, in the method for automatically debugging audio parameters of the recording channel of the body camera described in the present application, the step of obtaining audio data of a preset time period of the body camera, extracting background noise data and volume data, and processing the background noise data to obtain scene category feature data includes:

[0012] Obtain audio data of the body camera during a preset time period, and extract background noise data and volume data;

[0013] The background noise data includes frequency energy distribution data and sound pressure level data;

[0014] The volume data includes pickup volume data and intercom volume data;

[0015] The frequency energy distribution data and the sound pressure level data are input into a preset noise scene recognition model for processing to obtain scene category feature data.

[0016] Optionally, in the method for automatically debugging audio parameters of a body camera recording channel described in the present application, the processing according to the scene category feature data to obtain a volume threshold value, and comparing it with the volume data to obtain a volume deviation rate includes:

[0017] According to the scene category feature data, a preset volume threshold setting list is searched to obtain a volume threshold;

[0018] The volume data is compared with the volume threshold to obtain a volume deviation rate, including a sound pickup volume deviation rate and a talkback volume deviation rate.

[0019] Optionally, in the method for automatically debugging audio parameters of the recording channel of the body camera described in the present application, the step of obtaining the working instructions of the body camera, and processing the working instructions in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters includes:

[0020] Obtain working instructions of the body camera, including pickup instructions or intercom instructions;

[0021] The preset audio parameter setting database is queried according to the scene category feature data and the volume deviation rate to obtain initial audio parameters, including pickup audio parameters corresponding to the pickup instruction and intercom audio parameters corresponding to the intercom instruction.

[0022] Optionally, in the method for automatically debugging audio parameters of the recording channel of the body camera described in the present application, the method of performing long-distance sound pickup or intercom according to the audio parameters, and obtaining real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters includes:

[0023] Performing long-distance sound pickup or intercom according to the audio parameters, acquiring real-time environmental audio data, and extracting audio feature data according to the real-time environmental audio data;

[0024] The audio feature data includes real-time sound loudness mean and real-time background noise data, and the real-time background noise data includes noise frequency energy distribution data and noise sound pressure level data;

[0025] Inputting the noise frequency energy distribution data and the noise sound pressure level data into a preset noise scene recognition model for processing to obtain real-time scene category feature data;

[0026] The audio parameters are adjusted according to the real-time sound loudness mean and the real-time scene category feature data through a preset audio parameter optimization database to obtain audio optimization parameters, including pickup audio optimization parameters corresponding to the pickup instruction and intercom audio optimization parameters corresponding to the intercom instruction.

[0027] Optionally, the method for automatically debugging audio parameters of the recording channel of the body camera described in the present application further includes:

[0028] Acquire the audio data collected during a preset time period after the audio optimization parameters are implemented, and extract the audio signal-to-noise ratio, the audio harmonic distortion data, and the speech intelligibility rate based on the audio data collected;

[0029] Processing is performed according to the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate to obtain a sound pickup quality evaluation index;

[0030] Performing a threshold comparison between the sound pickup quality evaluation index and a preset quality evaluation threshold;

[0031] If it is less than or equal to the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified;

[0032] If it is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

[0033] In a second aspect, the present application provides a system for automatically debugging audio parameters of a recording channel of a law enforcement instrument, the system comprising: a memory and a processor, the memory comprising a program of an automatic debugging method for audio parameters of a recording channel of a law enforcement instrument, and the program of the automatic debugging method for audio parameters of a recording channel of a law enforcement instrument when executed by the processor implements the following steps:

[0034] Acquire the audio data of the body camera during a preset time period, extract the background noise data and volume data, process the background noise data, and obtain the scene category feature data;

[0035] Processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate;

[0036] Obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters;

[0037] Performing long-distance sound pickup or intercom according to the audio parameters, and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters;

[0038] Long-distance sound pickup or intercom is performed according to the audio optimization parameters.

[0039] Optionally, in the automatic debugging system for audio parameters of the recording channel of the body camera described in the present application, the audio data of the body camera in a preset time period is obtained, and the background noise data and volume data are extracted, and the background noise data is processed to obtain the scene category feature data, including:

[0040] Obtain audio data of the body camera during a preset time period, and extract background noise data and volume data;

[0041] The background noise data includes frequency energy distribution data and sound pressure level data;

[0042] The volume data includes pickup volume data and intercom volume data;

[0043] The frequency energy distribution data and the sound pressure level data are input into a preset noise scene recognition model for processing to obtain scene category feature data.

[0044] Optionally, in the automatic debugging system for audio parameters of the recording channel of the body camera described in the present application, processing is performed according to the scene category feature data to obtain a volume threshold, and the volume deviation rate is obtained by comparing it with the volume data, including:

[0045] According to the scene category feature data, a preset volume threshold setting list is searched to obtain a volume threshold;

[0046] The volume data is compared with the volume threshold to obtain a volume deviation rate, including a sound pickup volume deviation rate and a talkback volume deviation rate.

[0047] In the third aspect, the present application also provides a computer-readable storage medium, which stores a method program for automatically debugging the audio parameters of the recording channel of a law enforcement device. When the method program for automatically debugging the audio parameters of the recording channel of a law enforcement device is executed by a processor, the steps of the method for automatically debugging the audio parameters of the recording channel of a law enforcement device as described in any of the above items are implemented.

[0048] From the above, it can be seen that the method, system and medium for automatic debugging of the audio parameters of the recording channel of the law enforcement device provided in this application obtain audio parameters according to the working scenario and volume deviation rate of the law enforcement device, and optimize the parameters according to the audio feature data, thereby realizing automatic calling and intelligent optimization of the audio parameters of different working instructions of the law enforcement device, solving the conflict problem between long-distance sound pickup and intercom howling of the law enforcement device, and improving the adaptability of the law enforcement device.

[0049] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 A flowchart of a method for automatically debugging audio parameters of a law enforcement device recording channel provided in an embodiment of the present application;

[0052] Figure 2 A flowchart of obtaining scene category feature data of a method for automatically debugging audio parameters of a law enforcement device recording channel provided in an embodiment of the present application;

[0053] Figure 3 A flowchart of obtaining the volume deviation rate of the method for automatically debugging the audio parameters of the recording channel of the law enforcement device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0055] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0056] Please refer to Figure 1 , Figure 1 The flowchart of the method for automatically debugging the audio parameters of the recording channel of the law enforcement device in some embodiments of the present application is shown in FIG. The method for automatically debugging the audio parameters of the recording channel of the law enforcement device is used in a terminal device, such as a computer, a mobile phone terminal, etc. The method for automatically debugging the audio parameters of the recording channel of the law enforcement device comprises the following steps:

[0057] S11, obtaining audio data of a preset time period of the body camera, extracting background noise data and volume data, processing the background noise data, and obtaining scene category feature data;

[0058] S12, processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate;

[0059] S13, obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters;

[0060] S14, performing long-distance sound pickup or intercom according to the audio parameters, and obtaining real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters;

[0061] S15. Performing long-distance sound pickup or intercom according to the audio optimization parameters.

[0062] It should be noted that in order to call different audio parameters according to different scenarios and different work instructions, the audio data of the preset time period of the law enforcement instrument is first obtained, and the background noise data and volume data are extracted. The scene category feature data is queried based on the background noise data. The corresponding volume threshold is obtained based on the scene category feature data query, and then compared with the volume data to obtain the volume deviation rate. The preset audio parameters are called in combination with the long-distance sound pickup or intercom instructions, and long-distance sound pickup or intercom is performed according to the obtained audio parameters, and real-time environmental audio data is further obtained to confirm the changes in the current recording or intercom environment. The audio parameters are further adjusted according to the audio feature data extracted from the real-time environmental audio data to obtain audio optimization parameters, and finally long-distance sound pickup or intercom is performed according to the audio optimization parameters.

[0063] Please refer to Figure 2 , Figure 2 The flowchart of the method for automatically debugging the audio parameters of the recording channel of the body camera in some embodiments of the present application is to obtain scene category feature data. According to the embodiment of the present invention, the method of obtaining the audio data of the body camera in a preset time period, extracting the background noise data and the volume data, and processing the background noise data to obtain the scene category feature data includes:

[0064] S21, obtaining audio data of a preset time period of the body camera, and extracting background noise data and volume data;

[0065] S22, the background noise data includes frequency energy distribution data and sound pressure level data;

[0066] S23, the volume data includes pickup volume data and intercom volume data;

[0067] S24, inputting the frequency energy distribution data and the sound pressure level data into a preset noise scene recognition model for processing to obtain scene category feature data.

[0068] It should be noted that since the environment for long-distance sound pickup or intercom of the law enforcement instrument changes dynamically, before determining the audio parameters, it is necessary to confirm the scene category. First, the audio data of the preset time period of the law enforcement instrument is obtained, and the background noise data including frequency energy distribution data and sound pressure level data are extracted, including volume data of sound pickup volume data and intercom volume data. Among them, the frequency energy distribution data refers to the energy proportion of noise in each frequency band. The sound pressure level data is obtained by technical personnel in this field through a sliding average algorithm based on the actual measured sound pressure combined with the preset standard reference sound pressure, reflecting the size of the pressure fluctuation of the sound relative to the reference sound pressure. The frequency energy distribution data and the sound pressure level data are input into the preset noise scene recognition model for processing to obtain scene category feature data. The scene category feature data refers to the scene categories of residential areas, commercial pedestrian streets, factory workshops, hospitals, school playgrounds, parks and libraries. Among them, the preset noise scene recognition model is obtained by obtaining a large number of historical samples of frequency energy distribution data and sound pressure level data as well as corresponding scene category feature data for training.

[0069] Please refer to Figure 3 , Figure 3 The present invention is a flowchart of obtaining the volume deviation rate of the method for automatically debugging the audio parameters of the recording channel of the body camera in some embodiments of the present invention. According to the embodiment of the present invention, the volume threshold is obtained by processing the scene category feature data, and the volume deviation rate is obtained by comparing it with the volume data, including:

[0070] S31, querying a preset volume threshold setting list to obtain a volume threshold according to the scene category feature data;

[0071] S32. Compare the volume data with the volume threshold to obtain a volume deviation rate, including a sound pickup volume deviation rate and a talkback volume deviation rate.

[0072] It should be noted that when the law enforcement device faces complex scenes, the pickup or intercom volume also changes dynamically. The volume deviation rate is obtained by comparing the current volume with the volume threshold where howling or unclear pickup occurs. The volume deviation rate refers to the ratio of the absolute value of the difference between the volume data and the volume threshold to the volume threshold. The volume threshold is obtained by querying the preset volume threshold setting list through the obtained scene category feature data, and the preset volume threshold setting list is obtained by querying the preset audio parameter automatic debugging platform.

[0073] According to an embodiment of the present invention, the method of obtaining the working instruction of the body camera and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain the corresponding audio parameters includes:

[0074] Obtain working instructions of the body camera, including pickup instructions or intercom instructions;

[0075] The preset audio parameter setting database is queried according to the scene category feature data and the volume deviation rate to obtain initial audio parameters, including pickup audio parameters corresponding to the pickup instruction and intercom audio parameters corresponding to the intercom instruction.

[0076] It should be noted that different audio parameters are called according to different working instructions of the body law enforcement instrument, and the preset audio parameter setting database is queried according to the obtained scene category feature data and volume deviation rate to obtain initial audio parameters including the pickup audio parameters corresponding to the pickup instructions and the intercom audio parameters corresponding to the intercom instructions, including MIC sensitivity, echo cancellation parameters and noise suppression parameters. The preset audio parameter setting database is obtained by querying the preset audio parameter automatic debugging platform.

[0077] According to an embodiment of the present invention, performing long-distance sound pickup or intercom according to the audio parameters and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, adjusting the audio parameters according to the audio feature data, and obtaining audio optimization parameters include:

[0078] Performing long-distance sound pickup or intercom according to the audio parameters, acquiring real-time environmental audio data, and extracting audio feature data according to the real-time environmental audio data;

[0079] The audio feature data includes real-time sound loudness mean and real-time background noise data, and the real-time background noise data includes noise frequency energy distribution data and noise sound pressure level data;

[0080] Inputting the noise frequency energy distribution data and the noise sound pressure level data into a preset noise scene recognition model for processing to obtain real-time scene category feature data;

[0081] The audio parameters are adjusted according to the real-time sound loudness mean and the real-time scene category feature data through a preset audio parameter optimization database to obtain audio optimization parameters, including pickup audio optimization parameters corresponding to the pickup instruction and intercom audio optimization parameters corresponding to the intercom instruction.

[0082] It should be noted that after obtaining the audio parameters, long-distance sound pickup or intercom is performed. Due to the dynamic variability of the environment, real-time monitoring is required, and the audio parameters are optimized according to the changes. First, the real-time environmental audio data is obtained, and audio feature data including the real-time sound loudness mean and the real-time background noise data are extracted, wherein the real-time sound loudness mean is calculated by a technician in this field according to a variety of environmental sound intensities and frequency changes by using an adaptive loudness calculation algorithm, and the noise frequency energy distribution data and the noise sound pressure level data of the real-time background noise data are processed in combination with a preset noise scene recognition model to obtain real-time scene category feature data for confirming whether the scene has changed, and finally, the audio parameters are adjusted through a preset audio parameter optimization database according to the obtained real-time sound loudness mean and real-time scene category feature data, and audio optimization parameters including the sound pickup audio optimization parameters corresponding to the sound pickup instruction and the intercom audio optimization parameters corresponding to the intercom instruction are obtained, wherein the preset audio parameter optimization database is obtained by querying the preset audio parameter automatic debugging platform.

[0083] According to an embodiment of the present invention, it also includes:

[0084] Acquire the audio data collected during a preset time period after the audio optimization parameters are implemented, and extract the audio signal-to-noise ratio, the audio harmonic distortion data, and the speech intelligibility rate based on the audio data collected;

[0085] Processing is performed according to the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate to obtain a sound pickup quality evaluation index;

[0086] Performing a threshold comparison between the sound pickup quality evaluation index and a preset quality evaluation threshold;

[0087] If it is less than or equal to the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified;

[0088] If it is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

[0089] It should be noted that after determining the audio optimization parameters, the body camera is used to perform long-distance sound pickup. In order to evaluate the sound pickup effect, the sound pickup audio data within a preset time period is first obtained, and the sound pickup signal-to-noise ratio, sound pickup harmonic distortion data and speech intelligibility are extracted. Among them, the speech intelligibility rate refers to the ratio of the number of correctly recognized words in the picked-up audio to the total number of words. After further processing, the sound pickup quality evaluation index is obtained.

[0090] The sound pickup quality evaluation index calculation formula is:

[0091] ;

[0092] in, It is the sound pickup quality evaluation index. , , They are the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate. , The preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset audio parameter automatic debugging platform);

[0093] The obtained sound pickup quality evaluation index is compared with the preset quality evaluation threshold. In this embodiment, the preset quality evaluation threshold is set to (0, 0.7] and (0.7, 1], which correspond to unqualified sound pickup quality and qualified sound pickup quality, respectively. For example, if the obtained sound pickup quality evaluation index is 0.6, which is less than the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified. If the obtained sound pickup quality evaluation index is 0.8, which is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

[0094] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0095] Obtain volume data from multiple direction collection terminals of the body camera;

[0096] The volume data and the volume threshold are processed in combination with a corresponding preset sampling weight coefficient to obtain a volume deviation optimization rate.

[0097] It should be noted that the body camera needs to face people from different directions, and a single volume collection device may have inaccurate judgment of the volume. Therefore, the volume data collected by the body camera in multiple directions is combined with the volume threshold and the corresponding preset sampling weight coefficient to obtain the volume deviation optimization rate.

[0098] The volume deviation optimization rate calculation formula is:

[0099] ;

[0100] in, is the volume deviation optimization rate, , are the volume data of the i-th collection end and the corresponding preset sampling weight coefficient, n is the number of collection ends, is the volume threshold.

[0101] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0102] Obtain the voice quality data of the body camera intercom command within the preset time period after the audio optimization parameters are implemented, including intercom signal-to-noise ratio, intercom harmonic distortion and voice clarity data;

[0103] According to the intercom signal-to-noise ratio, intercom harmonic distortion and speech clarity data, the intercom signal-to-noise ratio, the intercom harmonic distortion and the speech clarity data are respectively compared with the preset signal-to-noise ratio reference value, the harmonic distortion threshold value and the speech clarity requirement value to obtain the signal-to-noise ratio deviation rate, the harmonic distortion deviation rate and the clarity deviation rate;

[0104] Processing is performed according to the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate to obtain an intercom voice quality evaluation index;

[0105] Comparing the intercom voice quality evaluation index with a preset intercom voice index threshold;

[0106] If it is less than or equal to the preset intercom voice index threshold, the intercom call is judged to be unqualified;

[0107] If it is greater than the preset intercom voice index threshold, the intercom call is determined to be qualified.

[0108] It should be noted that in order to evaluate the intercom voice call quality, voice quality data including intercom signal-to-noise ratio, intercom harmonic distortion and voice clarity data are obtained, and compared with the preset signal-to-noise ratio reference value, harmonic distortion threshold and voice clarity requirement value respectively, to obtain the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate, wherein the signal-to-noise ratio deviation rate refers to the ratio of the absolute value of the difference between the intercom signal-to-noise ratio and the signal-to-noise ratio reference value to the signal-to-noise ratio reference value. Similarly, the harmonic distortion deviation rate and clarity deviation rate can be obtained, and further processed to obtain the intercom voice quality evaluation index;

[0109] The intercom voice quality evaluation index calculation formula is:

[0110] ;

[0111] in, It is the intercom voice quality evaluation index. , , They are the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate, The preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset audio parameter automatic debugging platform);

[0112] The obtained intercom voice quality evaluation index is compared with the preset intercom voice index threshold. In this embodiment, the preset intercom voice index threshold is set to (0, 0.85] and (0.85, 1], which correspond to unqualified intercom calls and qualified intercom calls, respectively. For example, if the obtained intercom voice quality evaluation index is 0.8, which is less than the preset intercom voice index threshold, the intercom call is judged to be unqualified. If the obtained intercom voice quality evaluation index is 0.9, which is greater than the preset intercom voice index threshold, the intercom call is judged to be qualified.

[0113] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0114] Obtain the sound pickup quality pass rate within a preset time period;

[0115] Comparing the sound pickup quality pass rate with a preset sound pickup quality pass rate threshold;

[0116] If it is less than or equal to the preset sound pickup quality pass rate threshold, shorten the collection time interval according to the preset time interval;

[0117] If it is greater than the preset sound pickup quality pass rate threshold, the collection time interval is extended according to the preset time interval.

[0118] It should be noted that after obtaining the audio optimization parameters, it is necessary to regularly inspect the recording quality to ensure that the recording quality is qualified. In order to reduce unnecessary computing resource consumption, it is necessary to obtain the sound pickup quality qualification rate within a preset time period. The sound pickup quality qualification rate refers to the ratio of the number of sound pickup quality qualification times to the total number of sampling times, and then compare the sound pickup quality qualification rate with the preset sound pickup quality qualification rate threshold. In this embodiment, the preset sound pickup quality qualification rate threshold is set to (0, 0.8], (0.8, 1]. For example, the sound pickup quality qualification rate is 0.7, which is less than the preset sound pickup quality qualification rate threshold, indicating that the recording quality is insufficient and the audio optimization parameters need to be further evaluated. In order to evaluate more accurately, it is necessary to shorten the collection time interval according to the preset time interval. If the sound pickup quality qualification rate is 0.9, which is greater than the preset sound pickup quality qualification rate threshold, it means that the recording quality is good. In order to reduce unnecessary computing resource consumption, the collection time interval is extended according to the preset time interval.

[0119] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0120] Obtain the intercom call pass rate within a preset time period;

[0121] Comparing the intercom call pass rate with a preset intercom call pass rate threshold;

[0122] If it is less than or equal to the preset intercom call pass rate threshold, shorten the collection time interval according to the preset time interval;

[0123] If it is greater than the preset intercom call pass rate threshold, the collection time interval is extended according to the preset time interval.

[0124] It should be noted that after obtaining the audio optimization parameters, it is necessary to regularly inspect the intercom call quality to ensure that the intercom quality is qualified. In order to reduce unnecessary computing resource consumption, it is necessary to obtain the intercom quality qualification rate within the preset time period. The intercom quality qualification rate refers to the ratio of the number of qualified intercom calls to the total number of sampling times, and then compare the intercom quality qualification rate with the preset intercom quality qualification rate threshold. In this embodiment, the preset intercom quality qualification rate threshold is set to (0, 0.8], (0.8, 1]. For example, the intercom quality qualification rate is 0.7, which is less than the preset intercom quality qualification rate threshold, indicating that the intercom quality is insufficient and the audio optimization parameters need to be further evaluated. In order to evaluate more accurately, it is necessary to shorten the collection time interval according to the preset time interval. If the intercom quality qualification rate is 0.9, which is greater than the intercom quality qualification rate threshold, it means that the intercom call quality is good. In order to reduce unnecessary computing resource consumption, the collection time interval is extended according to the preset time interval.

[0125] The present invention also discloses an automatic debugging system for audio parameters of a recording channel of a law enforcement instrument, comprising a memory and a processor, wherein the memory comprises an automatic debugging method program for audio parameters of a recording channel of a law enforcement instrument, and when the automatic debugging method program for audio parameters of a recording channel of a law enforcement instrument is executed by the processor, the following steps are implemented:

[0126] Acquire the audio data of the body camera during a preset time period, extract the background noise data and volume data, process the background noise data, and obtain the scene category feature data;

[0127] Processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate;

[0128] Obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters;

[0129] Performing long-distance sound pickup or intercom according to the audio parameters, and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters;

[0130] Long-distance sound pickup or intercom is performed according to the audio optimization parameters.

[0131] It should be noted that in order to call different audio parameters according to different scenarios and different work instructions, the audio data of the preset time period of the law enforcement instrument is first obtained, and the background noise data and volume data are extracted. The scene category feature data is queried based on the background noise data. The corresponding volume threshold is obtained based on the scene category feature data query, and then compared with the volume data to obtain the volume deviation rate. The preset audio parameters are called in combination with the long-distance sound pickup or intercom instructions, and long-distance sound pickup or intercom is performed according to the obtained audio parameters, and real-time environmental audio data is further obtained to confirm the changes in the current recording or intercom environment. The audio parameters are further adjusted according to the audio feature data extracted from the real-time environmental audio data to obtain audio optimization parameters, and finally long-distance sound pickup or intercom is performed according to the audio optimization parameters.

[0132] According to an embodiment of the present invention, the method of obtaining audio data of a body camera in a preset time period, extracting background noise data and volume data, and processing the background noise data to obtain scene category feature data includes:

[0133] Obtain audio data of the body camera during a preset time period, and extract background noise data and volume data;

[0134] The background noise data includes frequency energy distribution data and sound pressure level data;

[0135] The volume data includes pickup volume data and intercom volume data;

[0136] The frequency energy distribution data and the sound pressure level data are input into a preset noise scene recognition model for processing to obtain scene category feature data.

[0137] It should be noted that since the environment for long-distance sound pickup or intercom of the law enforcement instrument changes dynamically, before determining the audio parameters, it is necessary to confirm the scene category. First, the audio data of the preset time period of the law enforcement instrument is obtained, and the background noise data including frequency energy distribution data and sound pressure level data are extracted, including volume data of sound pickup volume data and intercom volume data. Among them, the frequency energy distribution data refers to the energy proportion of noise in each frequency band. The sound pressure level data is obtained by technical personnel in this field through a sliding average algorithm based on the actual measured sound pressure combined with the preset standard reference sound pressure, reflecting the size of the pressure fluctuation of the sound relative to the reference sound pressure. The frequency energy distribution data and the sound pressure level data are input into the preset noise scene recognition model for processing to obtain scene category feature data. The scene category feature data refers to the scene categories of residential areas, commercial pedestrian streets, factory workshops, hospitals, school playgrounds, parks and libraries. Among them, the preset noise scene recognition model is obtained by obtaining a large number of historical samples of frequency energy distribution data and sound pressure level data as well as corresponding scene category feature data for training.

[0138] According to an embodiment of the present invention, the step of processing the scene category feature data to obtain a volume threshold, and comparing the volume threshold with the volume data to obtain a volume deviation rate includes:

[0139] According to the scene category feature data, a preset volume threshold setting list is searched to obtain a volume threshold;

[0140] The volume data is compared with the volume threshold to obtain a volume deviation rate, including a sound pickup volume deviation rate and a talkback volume deviation rate.

[0141] It should be noted that when the law enforcement device faces complex scenes, the pickup or intercom volume also changes dynamically. The volume deviation rate is obtained by comparing the current volume with the volume threshold where howling or unclear pickup occurs. The volume deviation rate refers to the ratio of the absolute value of the difference between the volume data and the volume threshold to the volume threshold. The volume threshold is obtained by querying the preset volume threshold setting list through the obtained scene category feature data, and the preset volume threshold setting list is obtained by querying the preset audio parameter automatic debugging platform.

[0142] According to an embodiment of the present invention, the method of obtaining the working instruction of the body camera and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain the corresponding audio parameters includes:

[0143] Obtain working instructions of the body camera, including pickup instructions or intercom instructions;

[0144] The preset audio parameter setting database is queried according to the scene category feature data and the volume deviation rate to obtain initial audio parameters, including pickup audio parameters corresponding to the pickup instruction and intercom audio parameters corresponding to the intercom instruction.

[0145] It should be noted that different audio parameters are called according to different working instructions of the body law enforcement instrument, and the preset audio parameter setting database is queried according to the obtained scene category feature data and volume deviation rate to obtain initial audio parameters including the pickup audio parameters corresponding to the pickup instructions and the intercom audio parameters corresponding to the intercom instructions, including MIC sensitivity, echo cancellation parameters and noise suppression parameters. The preset audio parameter setting database is obtained by querying the preset audio parameter automatic debugging platform.

[0146] According to an embodiment of the present invention, performing long-distance sound pickup or intercom according to the audio parameters and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, adjusting the audio parameters according to the audio feature data, and obtaining audio optimization parameters include:

[0147] Performing long-distance sound pickup or intercom according to the audio parameters, acquiring real-time environmental audio data, and extracting audio feature data according to the real-time environmental audio data;

[0148] The audio feature data includes real-time sound loudness mean and real-time background noise data, and the real-time background noise data includes noise frequency energy distribution data and noise sound pressure level data;

[0149] Inputting the noise frequency energy distribution data and the noise sound pressure level data into a preset noise scene recognition model for processing to obtain real-time scene category feature data;

[0150] The audio parameters are adjusted according to the real-time sound loudness mean and the real-time scene category feature data through a preset audio parameter optimization database to obtain audio optimization parameters, including pickup audio optimization parameters corresponding to the pickup instruction and intercom audio optimization parameters corresponding to the intercom instruction.

[0151] It should be noted that after obtaining the audio parameters, long-distance sound pickup or intercom is performed. Due to the dynamic variability of the environment, real-time monitoring is required, and the audio parameters are optimized according to the changes. First, the real-time environmental audio data is obtained, and audio feature data including the real-time sound loudness mean and the real-time background noise data are extracted, wherein the real-time sound loudness mean is calculated by a technician in this field according to a variety of environmental sound intensities and frequency changes by using an adaptive loudness calculation algorithm, and the noise frequency energy distribution data and the noise sound pressure level data of the real-time background noise data are processed in combination with a preset noise scene recognition model to obtain real-time scene category feature data for confirming whether the scene has changed, and finally, the audio parameters are adjusted through a preset audio parameter optimization database according to the obtained real-time sound loudness mean and real-time scene category feature data, and audio optimization parameters including the sound pickup audio optimization parameters corresponding to the sound pickup instruction and the intercom audio optimization parameters corresponding to the intercom instruction are obtained, wherein the preset audio parameter optimization database is obtained by querying the preset audio parameter automatic debugging platform.

[0152] According to an embodiment of the present invention, it also includes:

[0153] Acquire the audio data collected during a preset time period after the audio optimization parameters are implemented, and extract the audio signal-to-noise ratio, the audio harmonic distortion data, and the speech intelligibility rate based on the audio data collected;

[0154] Processing is performed according to the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate to obtain a sound pickup quality evaluation index;

[0155] Performing a threshold comparison between the sound pickup quality evaluation index and a preset quality evaluation threshold;

[0156] If it is less than or equal to the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified;

[0157] If it is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

[0158] It should be noted that after determining the audio optimization parameters, the body camera is used to perform long-distance sound pickup. In order to evaluate the sound pickup effect, the sound pickup audio data within a preset time period is first obtained, and the sound pickup signal-to-noise ratio, sound pickup harmonic distortion data and speech intelligibility are extracted. Among them, the speech intelligibility rate refers to the ratio of the number of correctly recognized words in the picked-up audio to the total number of words. After further processing, the sound pickup quality evaluation index is obtained.

[0159] The sound pickup quality evaluation index calculation formula is:

[0160] ;

[0161] in, It is the sound pickup quality evaluation index. , , They are the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate. , The preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset audio parameter automatic debugging platform);

[0162] The obtained sound pickup quality evaluation index is compared with the preset quality evaluation threshold. In this embodiment, the preset quality evaluation threshold is set to (0, 0.7] and (0.7, 1], which correspond to unqualified sound pickup quality and qualified sound pickup quality, respectively. For example, if the obtained sound pickup quality evaluation index is 0.6, which is less than the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified. If the obtained sound pickup quality evaluation index is 0.8, which is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

[0163] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0164] Obtain volume data from multiple direction collection terminals of the body camera;

[0165] The volume data and the volume threshold are processed in combination with a corresponding preset sampling weight coefficient to obtain a volume deviation optimization rate.

[0166] It should be noted that the body camera needs to face people from different directions, and a single volume collection device may have inaccurate judgment of the volume. Therefore, the volume data collected by the body camera in multiple directions is combined with the volume threshold and the corresponding preset sampling weight coefficient to obtain the volume deviation optimization rate.

[0167] The volume deviation optimization rate calculation formula is:

[0168] ;

[0169] in, is the volume deviation optimization rate, , are the volume data of the i-th collection end and the corresponding preset sampling weight coefficient, n is the number of collection ends, is the volume threshold.

[0170] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0171] Obtain the voice quality data of the body camera intercom command within the preset time period after the audio optimization parameters are implemented, including intercom signal-to-noise ratio, intercom harmonic distortion and voice clarity data;

[0172] According to the intercom signal-to-noise ratio, intercom harmonic distortion and speech clarity data, the intercom signal-to-noise ratio, the intercom harmonic distortion and the speech clarity data are respectively compared with the preset signal-to-noise ratio reference value, the harmonic distortion threshold value and the speech clarity requirement value to obtain the signal-to-noise ratio deviation rate, the harmonic distortion deviation rate and the clarity deviation rate;

[0173] Processing is performed according to the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate to obtain an intercom voice quality evaluation index;

[0174] Comparing the intercom voice quality evaluation index with a preset intercom voice index threshold;

[0175] If it is less than or equal to the preset intercom voice index threshold, the intercom call is judged to be unqualified;

[0176] If it is greater than the preset intercom voice index threshold, the intercom call is determined to be qualified.

[0177] It should be noted that in order to evaluate the intercom voice call quality, voice quality data including intercom signal-to-noise ratio, intercom harmonic distortion and voice clarity data are obtained, and compared with the preset signal-to-noise ratio reference value, harmonic distortion threshold and voice clarity requirement value respectively, to obtain the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate, wherein the signal-to-noise ratio deviation rate refers to the ratio of the absolute value of the difference between the intercom signal-to-noise ratio and the signal-to-noise ratio reference value to the signal-to-noise ratio reference value. Similarly, the harmonic distortion deviation rate and clarity deviation rate can be obtained, and further processed to obtain the intercom voice quality evaluation index;

[0178] The intercom voice quality evaluation index calculation formula is:

[0179] ;

[0180] in, It is the intercom voice quality evaluation index. , , They are the signal-to-noise ratio deviation rate, harmonic distortion deviation rate and clarity deviation rate, The preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset audio parameter automatic debugging platform);

[0181] The obtained intercom voice quality evaluation index is compared with the preset intercom voice index threshold. In this embodiment, the preset intercom voice index threshold is set to (0, 0.85] and (0.85, 1], which correspond to unqualified intercom calls and qualified intercom calls, respectively. For example, if the obtained intercom voice quality evaluation index is 0.8, which is less than the preset intercom voice index threshold, the intercom call is judged to be unqualified. If the obtained intercom voice quality evaluation index is 0.9, which is greater than the preset intercom voice index threshold, the intercom call is judged to be qualified.

[0182] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0183] Obtain the sound pickup quality pass rate within a preset time period;

[0184] Comparing the sound pickup quality pass rate with a preset sound pickup quality pass rate threshold;

[0185] If it is less than or equal to the preset sound pickup quality pass rate threshold, shorten the collection time interval according to the preset time interval;

[0186] If it is greater than the preset sound pickup quality pass rate threshold, the collection time interval is extended according to the preset time interval.

[0187] It should be noted that after obtaining the audio optimization parameters, it is necessary to regularly inspect the recording quality to ensure that the recording quality is qualified. In order to reduce unnecessary computing resource consumption, it is necessary to obtain the sound pickup quality qualification rate within a preset time period. The sound pickup quality qualification rate refers to the ratio of the number of sound pickup quality qualification times to the total number of sampling times, and then compare the sound pickup quality qualification rate with the preset sound pickup quality qualification rate threshold. In this embodiment, the preset sound pickup quality qualification rate threshold is set to (0, 0.8], (0.8, 1]. For example, the sound pickup quality qualification rate is 0.7, which is less than the preset sound pickup quality qualification rate threshold, indicating that the recording quality is insufficient and the audio optimization parameters need to be further evaluated. In order to evaluate more accurately, it is necessary to shorten the collection time interval according to the preset time interval. If the sound pickup quality qualification rate is 0.9, which is greater than the preset sound pickup quality qualification rate threshold, it means that the recording quality is good. In order to reduce unnecessary computing resource consumption, the collection time interval is extended according to the preset time interval.

[0188] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0189] Obtain the intercom call pass rate within a preset time period;

[0190] Comparing the intercom call pass rate with a preset intercom call pass rate threshold;

[0191] If it is less than or equal to the preset intercom call pass rate threshold, shorten the collection time interval according to the preset time interval;

[0192] If it is greater than the preset intercom call pass rate threshold, the collection time interval is extended according to the preset time interval.

[0193] It should be noted that after obtaining the audio optimization parameters, it is necessary to regularly inspect the intercom call quality to ensure that the intercom quality is qualified. In order to reduce unnecessary computing resource consumption, it is necessary to obtain the intercom quality qualification rate within the preset time period. The intercom quality qualification rate refers to the ratio of the number of qualified intercom calls to the total number of sampling times, and then compare the intercom quality qualification rate with the preset intercom quality qualification rate threshold. In this embodiment, the preset intercom quality qualification rate threshold is set to (0, 0.8], (0.8, 1]. For example, the intercom quality qualification rate is 0.7, which is less than the preset intercom quality qualification rate threshold, indicating that the intercom quality is insufficient and the audio optimization parameters need to be further evaluated. In order to evaluate more accurately, it is necessary to shorten the collection time interval according to the preset time interval. If the intercom quality qualification rate is 0.9, which is greater than the intercom quality qualification rate threshold, it means that the intercom call quality is good. In order to reduce unnecessary computing resource consumption, the collection time interval is extended according to the preset time interval.

[0194] A third aspect of the present invention provides a readable storage medium, which stores a method program for automatically debugging the audio parameters of a recording channel of a law enforcement device. When the method program for automatically debugging the audio parameters of a recording channel of a law enforcement device is executed by a processor, the steps of the method for automatically debugging the audio parameters of a recording channel of a law enforcement device as described in any of the above items are implemented.

[0195] The present invention discloses a method, system and medium for automatically debugging the audio parameters of a recording channel of a law enforcement instrument. By obtaining audio parameters according to the working scenario and volume deviation rate of the law enforcement instrument and optimizing the parameters according to audio feature data, the audio parameters of different working instructions of the law enforcement instrument can be automatically called and intelligently optimized, thereby solving the conflict problem between long-distance sound pickup and intercom howling of the law enforcement instrument and improving the adaptability of the law enforcement instrument.

[0196] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0197] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0198] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0199] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0200] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for automatically debugging audio parameters of a law enforcement device recording channel, characterized in that: The following steps are involved: Acquire the audio data of the body camera during a preset time period, extract the background noise data and volume data, process the background noise data, and obtain the scene category feature data; Processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate; Obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters; Performing long-distance sound pickup or intercom according to the audio parameters, and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters; Performing long-distance sound pickup or intercom according to the audio optimization parameters; The step of processing the scene category feature data to obtain a volume threshold, and comparing the volume threshold with the volume data to obtain a volume deviation rate includes: According to the scene category feature data, a preset volume threshold setting list is searched to obtain a volume threshold; Comparing the volume data with the volume threshold to obtain a volume deviation rate, including a pickup volume deviation rate and an intercom volume deviation rate; The method of performing long-distance sound pickup or intercom according to the audio parameters and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters includes: Performing long-distance sound pickup or intercom according to the audio parameters, acquiring real-time environmental audio data, and extracting audio feature data according to the real-time environmental audio data; The audio feature data includes real-time sound loudness mean and real-time background noise data, and the real-time background noise data includes noise frequency energy distribution data and noise sound pressure level data; Inputting the noise frequency energy distribution data and the noise sound pressure level data into a preset noise scene recognition model for processing to obtain real-time scene category feature data; The audio parameters are adjusted according to the real-time sound loudness mean and the real-time scene category feature data through a preset audio parameter optimization database to obtain audio optimization parameters, including pickup audio optimization parameters corresponding to the pickup instruction and intercom audio optimization parameters corresponding to the intercom instruction; Also includes: Obtain volume data from multiple direction collection terminals of the body camera; Processing the volume data and the volume threshold in combination with a corresponding preset sampling weight coefficient to obtain a volume deviation optimization rate; Also includes: Obtain the sound pickup quality pass rate within a preset time period; Comparing the sound pickup quality pass rate with a preset sound pickup quality pass rate threshold; If it is less than or equal to the preset sound pickup quality pass rate threshold, shorten the collection time interval according to the preset time interval; If it is greater than the preset sound pickup quality pass rate threshold, the collection time interval is extended according to the preset time interval.

2. The method for automatically debugging audio parameters of the recording channel of the law enforcement instrument according to claim 1 is characterized in that: The method of obtaining audio data of a preset time period of the body camera, extracting background noise data and volume data, and processing the background noise data to obtain scene category feature data includes: Obtain audio data of the body camera during a preset time period, and extract background noise data and volume data; The background noise data includes frequency energy distribution data and sound pressure level data; The volume data includes pickup volume data and intercom volume data; The frequency energy distribution data and the sound pressure level data are input into a preset noise scene recognition model for processing to obtain scene category feature data.

3. The method for automatically debugging audio parameters of the recording channel of the law enforcement instrument according to claim 1 is characterized in that: The method of obtaining the working instruction of the body camera and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain the corresponding audio parameters includes: Obtain working instructions of the body camera, including pickup instructions or intercom instructions; The preset audio parameter setting database is queried according to the scene category feature data and the volume deviation rate to obtain initial audio parameters, including pickup audio parameters corresponding to the pickup instruction and intercom audio parameters corresponding to the intercom instruction.

4. The method for automatically debugging audio parameters of the recording channel of the law enforcement instrument according to claim 1 is characterized in that: Also includes: Acquire the audio data collected during a preset time period after the audio optimization parameters are implemented, and extract the audio signal-to-noise ratio, the audio harmonic distortion data, and the speech intelligibility rate based on the audio data collected; Processing is performed according to the sound pickup signal-to-noise ratio, the sound pickup harmonic distortion data and the speech intelligibility rate to obtain a sound pickup quality evaluation index; Performing a threshold comparison between the sound pickup quality evaluation index and a preset quality evaluation threshold; If it is less than or equal to the preset quality evaluation threshold, the sound pickup quality is judged to be unqualified; If it is greater than the preset quality evaluation threshold, the sound pickup quality is judged to be qualified.

5. The audio parameter automatic debugging system of the law enforcement instrument recording channel is characterized by: The invention comprises a memory and a processor, wherein the memory comprises a method program for automatically debugging audio parameters of a recording channel of a law enforcement instrument, and when the method program for automatically debugging audio parameters of a recording channel of a law enforcement instrument is executed by the processor, the following steps are implemented: Acquire the audio data of the body camera during a preset time period, extract the background noise data and volume data, process the background noise data, and obtain the scene category feature data; Processing the scene category feature data to obtain a volume threshold, and comparing the threshold with the volume data to obtain a volume deviation rate; Obtaining a working instruction of the body camera, and processing the working instruction in combination with the scene category feature data and the volume deviation rate to obtain corresponding audio parameters; Performing long-distance sound pickup or intercom according to the audio parameters, and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters; Performing long-distance sound pickup or intercom according to the audio optimization parameters; The step of processing the scene category feature data to obtain a volume threshold, and comparing the volume threshold with the volume data to obtain a volume deviation rate includes: According to the scene category feature data, a preset volume threshold setting list is searched to obtain a volume threshold; Comparing the volume data with the volume threshold to obtain a volume deviation rate, including a pickup volume deviation rate and an intercom volume deviation rate; The method of performing long-distance sound pickup or intercom according to the audio parameters and acquiring real-time environmental audio data, extracting audio feature data according to the real-time environmental audio data, and adjusting the audio parameters according to the audio feature data to obtain audio optimization parameters includes: Performing long-distance sound pickup or intercom according to the audio parameters, acquiring real-time environmental audio data, and extracting audio feature data according to the real-time environmental audio data; The audio feature data includes real-time sound loudness mean and real-time background noise data, and the real-time background noise data includes noise frequency energy distribution data and noise sound pressure level data; Inputting the noise frequency energy distribution data and the noise sound pressure level data into a preset noise scene recognition model for processing to obtain real-time scene category feature data; The audio parameters are adjusted according to the real-time sound loudness mean and the real-time scene category feature data through a preset audio parameter optimization database to obtain audio optimization parameters, including pickup audio optimization parameters corresponding to the pickup instruction and intercom audio optimization parameters corresponding to the intercom instruction; Also includes: Obtain volume data from multiple direction collection terminals of the body camera; Processing the volume data and the volume threshold in combination with a corresponding preset sampling weight coefficient to obtain a volume deviation optimization rate; Also includes: Obtain the sound pickup quality pass rate within a preset time period; Comparing the sound pickup quality pass rate with a preset sound pickup quality pass rate threshold; If it is less than or equal to the preset sound pickup quality pass rate threshold, shorten the collection time interval according to the preset time interval; If it is greater than the preset sound pickup quality pass rate threshold, the collection time interval is extended according to the preset time interval.

6. The automatic debugging system for audio parameters of the recording channel of the law enforcement instrument according to claim 5 is characterized in that: The method of obtaining audio data of a preset time period of the body camera, extracting background noise data and volume data, and processing the background noise data to obtain scene category feature data includes: Obtain audio data of the body camera during a preset time period, and extract background noise data and volume data; The background noise data includes frequency energy distribution data and sound pressure level data; The volume data includes pickup volume data and intercom volume data; The frequency energy distribution data and the sound pressure level data are input into a preset noise scene recognition model for processing to obtain scene category feature data.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a method program for automatically debugging the audio parameters of the recording channel of the law enforcement device. When the method program for automatically debugging the audio parameters of the recording channel of the law enforcement device is executed by the processor, the steps of the method for automatically debugging the audio parameters of the recording channel of the law enforcement device as described in any one of claims 1 to 4 are implemented.

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