Audio adjustment method and system, electronic equipment and computer storage medium

Abstract

The embodiment of the invention provides an audio adjustment method and system, electronic equipment and a computer storage medium. Calling an artificial intelligence analysis model corresponding to at least one tone quality parameter according to at least one tone quality mode to perform comparative analysis and optimization on the digital audio signal so as to obtain parameter adjustment information and the digital audio signal optimized according to the parameter adjustment information, the sound quality parameter of the pickup device is adjusted according to the parameter adjustment information, so that intelligent adjustment of the sound quality of the pickup device is realized, and human intervention is reduced; and meanwhile, the digital audio signal optimized according to the parameter adjustment information is played back by using the loudspeaker equipment, so that the user can hear the optimized digital audio signal, and the audio adjustment efficiency is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of audio adjustment technology, and in particular to an audio adjustment method, system, electronic device and computer storage medium. Background Art

[0002] Most traditional microphones allow users to adjust the sound quality by themselves. Since most users do not have professional vocal knowledge, after completing manual adjustments, users need to record the sound in order to verify the adjustment effects. If the effects are not satisfactory, users need to make manual adjustments again and then re-record the sound for a new round of effect verification. This will require users to go through multiple adjustments and sound recording tests to achieve an adjustment effect that meets their expectations, resulting in a decrease in the user experience.

[0003] In the prior art, audio signal adjustment processing is all based on processing and adjustment of the input audio signal to generate an optimized audio signal. However, the input audio signal is generated by a recording device, and the gain, EQ, volume and other attribute controls of the recording device will directly generate the final (irreversible) audio signal. Therefore, the audio processing and adjustment method in the prior art cannot optimize the input of the recording device, and the adjustment effect is limited. The recording device is adjusted by the user himself, and the optimization effect is limited. Therefore, there is an urgent need for an audio device signal attribute parameter adjustment method that can obtain professional adjustment parameters based on the original audio for users to easily adjust or select. Summary of the invention

[0004] In view of this, an embodiment of the present application provides an audio adjustment method to at least partially solve the above-mentioned problem.

[0005] According to a first aspect of an embodiment of the present application, there is provided an audio adjustment method, which includes:

[0006] Collecting digital audio signals using a sound pickup device;

[0007] Calling at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare, analyze and optimize the digital audio signal to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information;

[0008] adjusting the sound quality parameter of the sound pickup device according to the parameter adjustment information;

[0009] The digital audio signal optimized according to the parameter adjustment information is played back using a speaker device.

[0010] Furthermore, the step of analyzing and optimizing the digital audio signal by calling at least one artificial intelligence analysis model of at least one sound quality parameter according to at least one timbre mode to obtain parameter adjustment information and optimizing the digital audio signal according to the parameter adjustment information comprises:

[0011] The steps of calling an EQ analysis and optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain EQ parameter adjustment information and a digital audio signal optimized according to the EQ parameter adjustment information,

[0012] The steps of calling the noise reduction analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain noise reduction parameter adjustment information and a digital audio signal optimized according to the noise reduction parameter adjustment information and / or

[0013] The step of calling a loudness analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain loudness parameter adjustment information and a digital audio signal optimized according to the loudness parameter adjustment information.

[0014] Furthermore, the step of calling the EQ analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain EQ parameter adjustment information and the digital audio signal optimized according to the EQ parameter adjustment information includes:

[0015] Retrieving multiple timbre benchmark models corresponding to different timbre modes from a large database;

[0016] and comparing and analyzing the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result;

[0017] Calculate the level difference corresponding to each frequency band of the digital audio signal according to the EQ comparison result as EQ parameter adjustment information;

[0018] According to the EQ parameter adjustment information, EQ adjustment optimization of different timbre modes is performed on the digital audio signal to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0019] Furthermore, the step of calling the noise reduction analysis optimization model according to at least one timbre mode to analyze and optimize the original audio signal to obtain noise reduction parameter adjustment information and a digital audio signal optimized according to the noise reduction parameter adjustment information includes:

[0020] Retrieving multiple noise reduction benchmark models corresponding to the timbre mode from a large database;

[0021] and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0022] Calculate the noise reduction level required by the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0023] The digital audio signal optimized according to the EQ parameter adjustment information is subjected to noise reduction optimization in different timbre modes to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0024] Furthermore, the step of calling the loudness analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain loudness parameter adjustment information and optimizing the digital audio signal according to the loudness parameter adjustment information includes:

[0025] Retrieving multiple loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database;

[0026] and comparing and analyzing the digital audio signal optimized according to the noise reduction parameter adjustment information with the multiple loudness parameter models to obtain loudness comparison results respectively;

[0027] Calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0028] According to the loudness parameter adjustment information, corresponding loudness adjustment is performed on the audio segment of the digital audio signal optimized according to the noise reduction parameter adjustment information to obtain a digital audio signal optimized according to the loudness parameter adjustment information.

[0029] Furthermore, the method also includes the following step: receiving mode instruction information input by a user.

[0030] In one embodiment, the step of adjusting the sound quality parameters of the sound pickup device according to the parameter adjustment information includes: adjusting the sound quality parameters of the sound pickup device using the parameter adjustment information corresponding to the mode instruction information; and

[0031] The step of using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information includes: using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information corresponding to the mode instruction information.

[0032] In one embodiment, the artificial intelligence analysis model is retrieved from the big data model based on the pattern instruction information.

[0033] In one embodiment, the parameter adjustment information and the digital audio signal optimized by the parameter adjustment information are selected from a plurality of the parameter adjustment information and the digital audio signal optimized by the parameter adjustment information according to the mode instruction information.

[0034] According to a second aspect of an embodiment of the present application, there is provided an audio adjustment system, comprising: a server, a user terminal, a sound pickup device and a sound speaker, wherein the sound pickup device comprises a signal transceiver module, a sound pickup module and an attribute adjustment module, the user terminal comprises a first original audio library, a first attribute parameter temporary storage library and a first adjusted audio temporary storage library, the server comprises a second attribute parameter temporary storage library, a second adjusted audio temporary storage library, an original audio library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the signal transceiver module is used to send the digital audio signals to the first original audio library, the first original audio library is used to forward the digital audio signals to the second original audio library of the server, and the comparison and analysis module is used to call an artificial intelligence analysis model of at least one sound quality parameter according to at least one timbre mode The digital audio signal is compared, analyzed and optimized to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information; the second adjustment audio temporary storage library is used to temporarily store the digital audio signal optimized according to the parameter adjustment information and forward it to the first adjustment audio temporary storage library; the second attribute parameter temporary storage library is used to temporarily store the parameter adjustment information and forward it to the first attribute parameter temporary storage library; the first adjustment audio temporary storage library is used to send the digital audio signal optimized according to the parameter adjustment information to a speaker device; the first attribute parameter temporary storage library is used to send the parameter adjustment information to the pickup device; the attribute adjustment module is used to adjust the sound quality parameters of the pickup module according to the parameter adjustment information; and the speaker device is used to play back the digital audio signal optimized according to the parameter adjustment information.

[0035] Furthermore, the user terminal also includes a mode instruction input module for receiving mode instruction information input by a user.

[0036] In one embodiment, the server also includes an adjustment output module, which is used to select at least one parameter adjustment information for adjusting the pickup module from multiple parameter adjustment information according to the mode instruction information; and is used to select at least one digital audio signal for playback in the speaker device from multiple digital audio signals optimized according to the parameter adjustment information according to the mode instruction information.

[0037] In one embodiment, the server also includes an adjustment input module for retrieving the artificial intelligence analysis model from the big data model according to the pattern instruction information.

[0038] In one embodiment, the first attribute parameter temporary storage library forwards corresponding parameter adjustment information according to the mode instruction information, and the first adjustment audio temporary storage library forwards corresponding digital audio signals optimized according to the parameter adjustment information according to the mode instruction information.

[0039] In one embodiment, the attribute adjustment module includes an attribute parameter allocation module, an EQ adjustment module, a gain amplifier and a noise reduction module. The attribute parameter allocation module is used to allocate parameter adjustment information received by the signal transceiver module to the EQ adjustment module, the gain amplifier and the noise reduction module. The EQ adjustment module is used to adjust the EQ parameter of the digital audio signal according to the parameter adjustment information. The gain amplifier is used to adjust the loudness parameter of the digital audio signal according to the parameter adjustment information. The noise reduction module is used to adjust the noise reduction level of the digital audio signal according to the parameter adjustment information.

[0040] In one embodiment, the comparison and analysis module includes a timbre comparison and optimization module, a clarity comparison and optimization module and / or a loudness comparison and optimization module.

[0041] Furthermore, the timbre comparison and optimization module includes:

[0042] The timbre comparison module is used to retrieve multiple timbre reference models corresponding to different timbre modes from a large database, and compare and analyze the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result.

[0043] a timbre adjustment parameter calculation module, used to calculate the level difference corresponding to each frequency band of the digital audio signal as EQ parameter adjustment information according to the EQ comparison result; and

[0044] The timbre optimization module is used to perform EQ adjustment optimization of different timbre modes on the digital audio signal according to the EQ parameter adjustment information to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0045] Furthermore, the clarity comparison optimization module includes:

[0046] A clarity comparison module, used for retrieving multiple noise reduction reference models corresponding to the timbre mode from a large database, and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0047] A clarity adjustment parameter calculation module, used to calculate the noise reduction level required for the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0048] The timbre optimization module is used to perform noise reduction optimization in different timbre modes on the digital audio signal optimized according to the EQ parameter adjustment information to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0049] Furthermore, the loudness comparison optimization module includes:

[0050] A loudness comparison module, configured to retrieve a plurality of loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database, and compare and analyze the digital audio signal optimized according to the noise reduction parameter adjustment information with the plurality of loudness parameter models to obtain loudness comparison results respectively;

[0051] A loudness adjustment parameter calculation module, used to calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0052] The loudness optimization module is used to perform corresponding loudness adjustment on the audio segment of the digital audio signal optimized according to the noise reduction parameter adjustment information according to the loudness parameter adjustment information to obtain the digital audio signal optimized according to the loudness parameter adjustment information.

[0053] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a sound pickup module, a property adjustment module, an original audio library, an adjusted audio temporary storage library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the original audio library is used to forward the digital audio signals to the comparison and analysis module, the comparison and analysis module is used to call at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare, analyze and optimize the digital audio signals to obtain parameter adjustment information and the digital audio signals optimized according to the parameter adjustment information, the adjusted audio library is used to send the digital audio signals optimized according to the parameter adjustment information to a speaker device, the property adjustment module is used to adjust the sound quality parameters of the sound pickup module according to the parameter adjustment information, and the speaker device is used to play back the digital audio signals optimized according to the parameter adjustment information.

[0054] In one embodiment, the attribute adjustment module includes an attribute parameter allocation module, an EQ adjustment module, a gain amplifier and a noise reduction module. The attribute parameter allocation module is used to allocate parameter adjustment information received by the signal transceiver module to the EQ adjustment module, the gain amplifier and the noise reduction module. The EQ adjustment module is used to adjust the EQ parameter of the digital audio signal according to the parameter adjustment information. The gain amplifier is used to adjust the loudness parameter of the digital audio signal according to the parameter adjustment information. The noise reduction module is used to adjust the noise reduction level of the digital audio signal according to the parameter adjustment information.

[0055] In one embodiment, the comparison and analysis module includes a timbre comparison and optimization module, a clarity comparison and optimization module and / or a loudness comparison and optimization module.

[0056] Furthermore, the timbre comparison and optimization module includes:

[0057] The timbre comparison module is used to retrieve multiple timbre reference models corresponding to different timbre modes from a large database, and compare and analyze the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result.

[0058] a timbre adjustment parameter calculation module, used to calculate the level difference corresponding to each frequency band of the digital audio signal as EQ parameter adjustment information according to the EQ comparison result; and

[0059] The timbre optimization module is used to perform EQ adjustment optimization of different timbre modes on the digital audio signal according to the EQ parameter adjustment information to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0060] Furthermore, the clarity comparison optimization module includes:

[0061] A clarity comparison module, used for retrieving multiple noise reduction reference models corresponding to the timbre mode from a large database, and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0062] A clarity adjustment parameter calculation module, used to calculate the noise reduction level required for the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0063] The timbre optimization module is used to perform noise reduction optimization in different timbre modes on the digital audio signal optimized according to the EQ parameter adjustment information to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0064] Furthermore, the loudness comparison optimization module includes:

[0065] A loudness comparison module, configured to retrieve a plurality of loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database, and compare and analyze the digital audio signal optimized according to the noise reduction parameter adjustment information with the plurality of loudness parameter models to obtain loudness comparison results respectively;

[0066] A loudness adjustment parameter calculation module, used to calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0067] The loudness optimization module is used to perform corresponding loudness adjustment on the audio segment of the digital audio signal optimized according to the noise reduction parameter adjustment information according to the loudness parameter adjustment information to obtain the digital audio signal optimized according to the loudness parameter adjustment information.

[0068] According to a fourth aspect of an embodiment of the present application, a computer storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the audio adjustment method as described in the first aspect is implemented.

[0069] According to the audio adjustment method provided in the embodiment of the present application, at least one artificial intelligence analysis model of sound quality parameters is called according to at least one timbre mode to compare, analyze and optimize the digital audio signal to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information, and the sound quality parameters of the sound pickup device are adjusted according to the parameter adjustment information, thereby realizing intelligent adjustment of the sound quality of the sound pickup device, reducing human intervention, and improving the efficiency of the user in adjusting the sound pickup device. At the same time, the present application uses a loudspeaker device to play back the digital audio signal optimized according to the parameter adjustment information, so that the user can hear the optimized digital audio signal, and the user can adjust the sound quality of the sound pickup device according to his or her own preferences by selecting the parameter adjustment information corresponding to the timbre mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0071] Figure 1 is a schematic diagram of an exemplary system applicable to the audio adjustment method of the embodiment of the present application;

[0072] Figure 2 is a flowchart of the steps of the audio adjustment method applicable to the embodiment of the present application;

[0073] Figure 3 is based on Figure 2 Detailed step flow chart of step S203;

[0074] Figure 4 is based on Figure 3 Detailed step flow chart of step S301;

[0075] Figure 5 is based on Figure 3 Detailed step flow chart of step S302;

[0076] Figure 6 is based on Figure 3 Detailed step flow chart of step S303;

[0077] Figure 7 is a structural block diagram of an audio adjustment system according to an embodiment of the present application;

[0078] Figure 8 is a structural block diagram of another audio adjustment system according to an embodiment of the present application;

[0079] Fig. 9 is a structural block diagram of another audio adjustment system according to an embodiment of the present application;

[0080] Fig.10 is a structural block diagram of a property adjustment module according to an embodiment of the present application;

[0081] Fig.11 is a structural block diagram of a comparison and analysis module according to an embodiment of the present application;

[0082] Fig.12 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0083] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present application, 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 part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the embodiments of the present application should fall within the scope of protection of the embodiments of the present application.

[0084] Moreover, some of the above terms may be used to express other meanings in addition to indicating orientation or positional relationships. For example, the term "on" may also be used to express a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in the present invention can be understood according to the specific circumstances. In addition, the terms "installed", "set", "provided with", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be an internal connection between two devices, elements, or components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0085] In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0086] The specific implementation of the embodiment of the present application is further explained below in conjunction with the accompanying drawings of the embodiment of the present application.

[0087] Figure 1 An exemplary system for the audio adjustment method of the embodiment of the present application is shown. Figure 1 As shown, the system 100 may include a server 102, one or more sound pickup devices 103, a speaker device 105, a communication network 104 and / or one or more user terminals 106. Figure 1 The example is a plurality of user terminals and a plurality of sound pickup devices.

[0088] The server 102 may be any suitable server for storing information, data, programs and / or any other suitable type of content. In some embodiments, the server 102 may perform any suitable function. For example, in some embodiments, the server 102 may be used to store, analyze and optimize digital audio signals. As an optional example, in some embodiments, the server 102 may receive the digital audio signal collected by the sound pickup device 103 uploaded by the user terminal 106 in response to a request from the user terminal 106. As another example, in some embodiments, the server 102 may be used to push the optimized digital audio signal and the parameter adjustment information for adjusting the sound pickup device 103 to the user terminal 106.

[0089] In some embodiments, the communication network 104 can be any suitable combination of one or more wired and / or wireless networks. For example, the communication network 104 can include any one or more of the following: the Internet, an intranet, a wide area network (WAN), a local area network (LAN), a wireless network, a digital subscriber line (DSL) network, a frame relay network, an asynchronous transfer mode (ATM) network, a virtual private network (VPN), and / or any other suitable communication network. The user terminal 106 can be connected to the communication network 104 via one or more communication links (e.g., communication link 112), and the communication network 104 can be linked to the server 102 via one or more communication links (e.g., communication link 114). The communication link can be any communication link suitable for transmitting data between the user terminal 106 and the server 102, such as a network link, a dial-up link, a wireless link, a hard-wired link, any other suitable communication link, or any suitable combination of such links.

[0090] In some embodiments, the user terminal 106 may include any suitable type of device. For example, in some embodiments, the user terminal 106 may include a mobile device, a tablet computer, a laptop computer, a desktop computer, a wearable computer, a game console, a media player, a vehicle entertainment system, and / or any other suitable type of user terminal. The user terminal 106 may be installed with software, for example, the digital audio signal collected by the sound pickup device 103 may be uploaded to the server 102, and the parameter adjustment information and the optimized digital audio signal generated by the server 102 may also be sent to the sound pickup device 103 and the speaker device 105.

[0091] In some embodiments, the sound pickup device 103 may include any suitable type of recording device, which can be used to collect digital audio signals and send them to the user terminal 106. For example, in some embodiments, the sound pickup device 103 may include a wireless microphone, a wired microphone and / or any other suitable type of recording device. The sound pickup device 103 may be connected to the user terminal 106 via a first short-range communication connection 115. The first short-range communication connection 115 may be a wired connection or a wireless connection.

[0092] In some embodiments, the speaker device 105 may include any suitable type of speaker, which may be used to receive and play back the digital audio signal sent by the user terminal 106. For example, in some embodiments, the speaker device 105 may include a wireless speaker, a wired speaker, and / or any other suitable type of speaker. The speaker device 105 may be connected to the user terminal 106 via a second short-range communication connection 116. The second short-range communication connection 116 may be a wired connection or a wireless connection.

[0093] Server 102 is illustrated as one device, but in some embodiments, any suitable number of devices may be used to perform the functions performed by server 102. For example, in some embodiments, multiple devices may be used to implement the functions performed by server 102. Alternatively, the functions of server 102 may be implemented using cloud services.

[0094] The audio adjustment method of this embodiment can be executed by any appropriate electronic device with audio signal processing capability, including but not limited to: a server, a mobile terminal (such as a mobile phone, a PAD, etc.), a PC, and a wireless microphone, etc.

[0095] Reference Figure 2 , is a flowchart of the steps of an audio adjustment method according to an embodiment of the present application. Figure 2 The specific process of an audio adjustment method of an embodiment of the present application is described. The audio adjustment method comprises the following steps:

[0096] S201: Collect digital audio signals using a sound pickup device.

[0097] As an example, the digital audio signal may be a digital audio file in a respective appropriate format. The sound pickup device may be various wired microphones or wireless microphones.

[0098] S203: Calling at least one artificial intelligence analysis model of sound quality parameter according to at least one timbre mode to compare, analyze and optimize the digital audio signal to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information.

[0099] In a specific example, the timbre mode may be, for example, “bright”, “mellow”, “rich”, etc. The sound quality parameters may include one or more of EQ, loudness, and noise reduction parameters.

[0100] In an embodiment of the present application, an analysis and comparison result can be obtained by analyzing and processing the digital audio signal through an artificial intelligence analysis model, and the analysis and comparison result can characterize the predicted category information of the digital audio signal in at least two different dimensions. In an embodiment of the present application, there is no restriction on the type of dimension predicted by the analysis and processing of the digital audio signal. For example, in some embodiments, the dimension predicted by the analysis and processing of the digital audio signal may include frequency dimension (pitch), tone dimension (loudness), timbre dimension (waveform), vocal dimension (noise reduction), instrumentation dimension, language dimension, type dimension, speed dimension, emotion dimension, etc. Among them, the frequency dimension can be used to distinguish the high and low frequencies of audio data, and its specific corresponding categories may include high frequency, medium frequency, low frequency, etc.; the pitch dimension can be used to distinguish the high and low pitches of audio data, and its specific corresponding categories may include treble, middle frequency, bass, etc.; the timbre dimension can be used to distinguish the timbre of audio data, and its specific corresponding categories may include bright, soft, high, sharp, etc.; the vocal dimension can be used to distinguish the vocal elements in audio data, and its specific corresponding categories may include male voice, female voice, children's voice, etc.; the instrument dimension can be used to distinguish the musical instruments used in the audio data, and its specific corresponding categories may include treble, middle frequency, bass, etc. The type dimension can include piano, guitar, violin, guzheng, etc.; the language dimension can be used to distinguish the language type corresponding to the audio data, and its specific corresponding categories can include Chinese, English, French, etc.; the type dimension can be used to distinguish the music type to which the audio data belongs, and its specific corresponding categories can include pop music, classical music, rock music, folk music, etc.; the speed dimension can be used to distinguish the melody speed of the audio data, and its specific corresponding categories can include fast, normal, slow, etc.; the emotion dimension can be used to distinguish the emotional tendencies reflected by the audio data, and its specific corresponding categories can include joy, sadness, passion, calmness, etc.

[0101] Of course, it can be understood that the above embodiments are only used to exemplify the analysis dimensions of the artificial intelligence analysis model in the embodiments of the present application, and are not meant to limit its actual implementation. Those skilled in the art can flexibly select the dimensions and the categories contained in the dimensions according to their needs, analyze and process the digital audio signal, and obtain the corresponding analysis and comparison results. The artificial intelligence analysis model may include multiple different types of analysis and optimization models, which analyze and optimize the digital audio signal for the aforementioned different dimensions respectively. The analysis and optimization model may include various types of benchmark models for audio adjustment, such as timbre benchmark models, noise reduction benchmark models, and loudness benchmark models, etc., which are used to compare and optimize the corresponding parameters of the digital audio signal respectively.

[0102] By using an artificial intelligence analysis model to compare and analyze the digital audio signal, parameter adjustment information can be obtained, for example, the level difference corresponding to each frequency band of the digital audio signal and the timbre reference model corresponding to the EQ parameter is used as the timbre parameter adjustment information, or the noise reduction reference model corresponding to each timbre mode and the digital audio signal are compared and analyzed to obtain the noise reduction level required for each timbre mode as the noise reduction parameter adjustment information, or the loudness parameter model corresponding to each timbre mode and the digital audio signal are compared and analyzed to obtain the loudness difference corresponding to each audio band as the loudness parameter adjustment information. In addition, the artificial intelligence analysis model also optimizes the digital audio signal using the parameter adjustment information to generate a digital audio signal optimized according to the parameter adjustment information. For example, in one embodiment, the digital audio signal can be optimized using the level difference corresponding to each frequency band of the digital audio signal (i.e., the EQ parameter adjustment information) in one of the multiple timbre reference models. For example, the level difference corresponding to each frequency band can be directly arithmetic-operated with the frequency band corresponding to the digital audio signal, so that the level amplitude of the frequency band corresponding to the digital audio signal approaches the level amplitude of the corresponding frequency band learned by the timbre reference model after training.

[0103] S205: Adjust the sound quality parameters of the sound pickup device according to the parameter adjustment information.

[0104] In an embodiment of the present application, the parameter adjustment information may include EQ parameter adjustment information, loudness parameter adjustment information and / or noise reduction parameter adjustment information, which are used to respectively adjust the EQ parameters, loudness parameters and / or noise reduction parameters of the sound pickup module of the sound pickup device, thereby adjusting the sound quality of the sound pickup device. During subsequent recording, the sound pickup module will use the new sound quality parameters to complete the collection of digital audio signals, thereby optimizing the original digital audio signals collected by the subsequent sound pickup device.

[0105] S207: Using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information.

[0106] In some examples, by using a loudspeaker device to play back a digital audio signal optimized according to the parameter adjustment information, the user can verify in real time through playback whether the digital audio signal optimized by the parameter adjustment information meets the requirements, thereby improving the efficiency of parameter adjustment. The user can also compare the effects of the digital audio signals optimized according to the parameter adjustment information corresponding to different timbre modes, thereby helping the user to select a favorite timbre mode, and then select the parameter adjustment information corresponding to the timbre mode that the user likes to adjust the sound pickup device, so that the user can complete the adjustment of the sound quality of the sound pickup device without professional tuning skills, and record a digital audio signal with a timbre that the user likes.

[0107] Figure 3 is based on Figure 2 In the embodiment, step S203 specifically includes the following steps:

[0108] S301: a step of calling an EQ analysis and optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain EQ parameter adjustment information and a digital audio signal optimized according to the EQ parameter adjustment information;

[0109] Specifically, different timbre modes correspond to different EQ analysis and optimization models. The EQ analysis and optimization models corresponding to multiple timbre modes can be called at the same time, and these EQ analysis and optimization models can be used to analyze and optimize the digital audio signal respectively, so as to obtain multiple sets of EQ parameter adjustment information and digital audio signals optimized according to the EQ parameter adjustment information.

[0110] S302: Calling a noise reduction analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain noise reduction parameter adjustment information and a digital audio signal optimized according to the noise reduction parameter adjustment information; and / or

[0111] Specifically, different timbre modes correspond to different noise reduction analysis and optimization models. The noise reduction analysis and optimization models corresponding to multiple timbre modes can be called at the same time, and these noise reduction analysis and optimization models can be used to analyze and optimize the digital audio signal respectively, so as to obtain multiple sets of noise reduction parameter adjustment information and digital audio signals optimized according to the noise reduction parameter adjustment information.

[0112] S303: a step of calling a loudness analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain loudness parameter adjustment information and a digital audio signal optimized according to the loudness parameter adjustment information.

[0113] Specifically, different timbre modes correspond to different analysis optimization models in the artificial intelligence analysis model. The analysis optimization models corresponding to multiple timbre modes can be called at the same time, and the digital audio signal can be analyzed and optimized using these analysis optimization models respectively, so as to obtain multiple sets of parameter adjustment information and digital audio signals optimized according to the parameter adjustment information. In some embodiments, all analysis optimization models corresponding to each timbre mode can be selected, and the digital audio signal can be compared and optimized in turn. For example, the EQ analysis optimization model, the noise reduction analysis optimization model, and the loudness analysis optimization model corresponding to each timbre mode can be used to compare and optimize the digital audio signal in turn, so as to obtain the optimized digital audio signal corresponding to each timbre mode, so that the user can select a favorite timbre mode from the playback of the optimized digital audio signal.

[0114] Figure 4 is based on Figure 3 In the embodiment, step S301 specifically includes the following steps:

[0115] S401: Retrieving multiple timbre benchmark models corresponding to different timbre modes from a large database;

[0116] S402: Compare and analyze the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result;

[0117] S403: Calculating level differences corresponding to each frequency band of the digital audio signal according to the EQ comparison result as EQ parameter adjustment information;

[0118] S404: performing EQ adjustment optimization of different timbre modes on the digital audio signal according to the EQ parameter adjustment information to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0119] It is easy to understand that the artificial intelligence analysis model includes multiple different types of analysis optimization models. The analysis optimization model can include various benchmark models for audio adjustment, such as timbre benchmark models, noise reduction benchmark models, and loudness benchmark models, etc., which are used to compare and optimize the corresponding parameters of digital audio signals.

[0120] By comparing the digital audio signal with multiple timbre reference models corresponding to the timbre mode, the level difference between the digital audio signal and each frequency band of each timbre reference model can be calculated based on the comparison result, and the level difference between the digital audio signal and each frequency band of each timbre reference model can be used as EQ parameter adjustment information to optimize the digital audio signal, and then the EQ parameter adjustment information is used to adjust the pickup device.

[0121] Bright timbre means that the level value of the high frequency band is high, mellow timbre means that the level value of the mid-frequency band is high, and deep timbre means that the level value of the low frequency band is high. The timbre benchmark model corresponding to different timbre modes can process digital audio signals through a deep learning network (such as a convolutional neural network CNN, a recurrent neural network RNN ​​or a Transformer) to analyze the interval of the level value of the corresponding frequency band in the audio signal. The model can be trained by inputting a large amount of audio data with labels. For example, in audio data with a "bright timbre" label, the level value of the high frequency band is obviously in a higher interval. The trained timbre benchmark model captures the dependency between the sequence data in the audio signal and the time series through the processing logic of the deep learning network, thereby completing the model construction. After the construction is completed, when the digital audio signal to be compared is input into the benchmark model, according to the user's optimization requirements, the timbre benchmark model optimizes the digital audio signal according to the analysis results of the level value of the frequency band of the digital audio signal. Specifically, when the user requires a bright timbre, the timbre benchmark model corresponding to the bright timbre can be used to calculate the difference between the level peak of the high frequency band of the digital audio signal and the benchmark level of the corresponding bright timbre label, generate an optimized digital audio signal according to the difference, and output the difference or the label corresponding to the difference as parameter adjustment information for adjusting the pickup device. The construction and working principle of the noise reduction benchmark model and the loudness benchmark model are similar. When the analysis and optimization model optimizes a digital audio signal, the high frequency, medium frequency, and low frequency parts can be marked respectively. The benchmark level provided by the timbre benchmark model can be in the form of a line segment, which is used to compare the parts of different frequency bands respectively; the comparison result can be the average of the difference between the level amplitude of the corresponding frequency band of the digital audio signal and the benchmark amplitude of the corresponding frequency band of the timbre benchmark model. When optimizing the digital audio signal, the analysis and optimization model can uniformly adjust the level amplitude of the corresponding frequency band, that is, use the average of the difference between the level amplitude of the corresponding frequency band of the digital audio signal and the reference amplitude of the corresponding frequency band of the timbre reference model to adjust the amplitude of each peak in the frequency band.

[0122] Figure 5 is based on Figure 3 In the embodiment, step S302 specifically includes the following steps:

[0123] S501: Retrieving multiple noise reduction benchmark models corresponding to the timbre mode from a large database;

[0124] S502: Compare and analyze the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0125] S503: Calculating the noise reduction level required by the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0126] S504: performing noise reduction optimization in different timbre modes on the digital audio signal optimized according to the EQ parameter adjustment information to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0127] It is easy to understand that by comparing multiple noise reduction reference models corresponding to the timbre mode with the digital audio signal, the noise reduction levels required for respectively calculating the timbre mode can be calculated based on the comparison results, and the noise reduction level mode is used as the noise reduction parameter adjustment information, and then the EQ parameter adjustment information is used to adjust the pickup device, thereby reducing noise and improving the sound quality of the digital audio signal collected by the pickup device.

[0128] Figure 6 is based on Figure 3 In the embodiment, step S303 specifically includes the following steps:

[0129] S601: Retrieving multiple loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database;

[0130] S602: Compare and analyze the digital audio signal optimized according to the noise reduction parameter adjustment information with the multiple loudness parameter models to obtain loudness comparison results respectively;

[0131] S603: Calculating loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0132] S604: Perform corresponding loudness adjustment on the audio segment of the digital audio signal optimized according to the loudness parameter adjustment information according to the loudness parameter adjustment information to obtain a digital audio signal optimized according to the loudness parameter adjustment information.

[0133] It is easy to understand that by comparing multiple loudness parameter models corresponding to the timbre mode with the digital audio signal, the noise reduction level mode corresponding to the requirements of each audio segment can be calculated according to the comparison results, and the noise reduction level mode is used as the noise reduction parameter adjustment information, and then the loudness parameter adjustment information is used to adjust the sound pickup device, thereby improving the sound quality of the digital audio signal collected by the sound pickup device.

[0134] In some embodiments, the method further comprises the following step: receiving mode instruction information input by a user. Specifically, the mode instruction information may include information of the timbre mode selected by the user, such as the ID, name or identification of the timbre mode selected by the user, so as to determine the corresponding parameter adjustment information according to the timbre mode selected by the user so as to complete the timbre adjustment of the sound pickup device.

[0135] In one embodiment, the step of adjusting the sound quality parameters of the sound pickup device according to the parameter adjustment information includes: adjusting the sound quality parameters of the sound pickup device using the parameter adjustment information corresponding to the mode instruction information; and the step of using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information includes: using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information corresponding to the mode instruction information. It is easy to understand that the user's mode instruction information contains information about the timbre mode selected by the user, and adjusting the sound quality parameters of the sound pickup device according to the parameter adjustment information corresponding to the timbre mode selected by the user can improve the efficiency of adjusting the sound quality parameters of the sound pickup device.

[0136] In one embodiment, the artificial intelligence analysis model is retrieved from the big data model according to the mode instruction information. It is easy to understand that selecting the artificial intelligence analysis model corresponding to the user's favorite timbre mode before using the artificial intelligence analysis model to compare and analyze the digital audio signal can reduce unnecessary analysis and comparison, improve the efficiency of the analysis and comparison of the digital audio signal, reduce energy consumption costs, and speed up processing.

[0137] Reference Figure 7, showing a structural block diagram of an audio adjustment system of an embodiment of the present application. In this example, the audio adjustment system includes: a server, a user terminal, a sound pickup device and a speaker device, wherein the sound pickup device includes a signal transceiver module, a sound pickup module and an attribute adjustment module, the user terminal includes a first original audio library, a first attribute parameter temporary storage library and a first adjustment audio temporary storage library, the server includes a second attribute parameter temporary storage library, a second adjustment audio temporary storage library, a second original audio library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the signal transceiver module is used to send the digital audio signals to the first original audio library, the first original audio library is used to forward the digital audio signals to the second original audio library of the server, and the comparison and analysis module is used to call at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to analyze the digital audio signals. The first property parameter temporary storage library is used to temporarily store the parameter adjustment information and forward it to the first property parameter temporary storage library; the first adjustment audio temporary storage library is used to send the digital audio signal optimized according to the parameter adjustment information to the speaker device; the first property parameter temporary storage library is used to send the parameter adjustment information to the pickup device; the property adjustment module is used to adjust the sound quality parameters of the pickup module according to the parameter adjustment information; and the speaker device is used to play back the digital audio signal optimized according to the parameter adjustment information.

[0138] The audio adjustment device of this embodiment is used to implement the corresponding audio adjustment methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here. In addition, the functional implementation of each module in the audio adjustment device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be repeated here.

[0139] Furthermore, the user terminal also includes a mode instruction input module for receiving mode instruction information input by a user.

[0140] Figure 8 FIG. 1 is a structural block diagram of another audio adjustment system according to an embodiment of the present application. Figure 8As shown, another audio adjustment system of an embodiment of the present application is basically the same as the aforementioned audio adjustment system. Only the differences are elaborated in detail below. In another audio adjustment system of an embodiment of the present application, the server also includes an adjustment output module, which is used to select at least one parameter adjustment information for adjusting the sound pickup module from multiple parameter adjustment information according to the mode instruction information; and is used to select at least one digital audio signal for playback in the speaker device from multiple digital audio signals optimized according to the parameter adjustment information according to the mode instruction information.

[0141] Fig. 9 FIG. 1 is a structural block diagram of another audio adjustment system according to an embodiment of the present application. Fig. 9 As shown, another audio adjustment system of an embodiment of the present application is basically the same as the aforementioned audio adjustment system, and only the differences are described in detail below. In another audio adjustment system of an embodiment of the present application, the server also includes an adjustment input module for calling the artificial intelligence analysis model from the big data model according to the mode instruction information.

[0142] In this embodiment, the first attribute parameter temporary storage library forwards corresponding parameter adjustment information according to the mode instruction information, and the first adjustment audio temporary storage library forwards corresponding digital audio signals optimized according to the parameter adjustment information according to the mode instruction information.

[0143] like Fig.10 As shown, in one embodiment, the attribute adjustment module includes an attribute parameter allocation module, an EQ adjustment module, a gain amplifier and a noise reduction module. The attribute parameter allocation module is used to allocate parameter adjustment information received by the signal transceiver module to the EQ adjustment module, the gain amplifier and the noise reduction module. The EQ adjustment module is used to adjust the EQ parameter of the digital audio signal according to the parameter adjustment information. The gain amplifier is used to adjust the loudness parameter of the digital audio signal according to the parameter adjustment information. The noise reduction module is used to adjust the noise reduction level of the digital audio signal according to the parameter adjustment information.

[0144] like Fig.11 As shown, in one embodiment, the comparison and analysis module includes a timbre comparison and optimization module, a clarity comparison and optimization module and / or a loudness comparison and optimization module.

[0145] Specifically, the timbre comparison and optimization module includes:

[0146] The timbre comparison module is used to retrieve multiple timbre reference models corresponding to different timbre modes from a large database, and compare and analyze the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result.

[0147] a timbre adjustment parameter calculation module, used to calculate the level difference corresponding to each frequency band of the digital audio signal as EQ parameter adjustment information according to the EQ comparison result; and

[0148] The timbre optimization module is used to perform EQ adjustment optimization of different timbre modes on the digital audio signal according to the EQ parameter adjustment information to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0149] Specifically, the clarity comparison optimization module includes:

[0150] A clarity comparison module, used for retrieving multiple noise reduction reference models corresponding to the timbre mode from a large database, and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0151] A clarity adjustment parameter calculation module, used to calculate the noise reduction level required for the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0152] The timbre optimization module is used to perform noise reduction optimization in different timbre modes on the digital audio signal optimized according to the EQ parameter adjustment information to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0153] Specifically, the loudness comparison optimization module includes:

[0154] A loudness comparison module, configured to retrieve a plurality of loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database, and compare and analyze the digital audio signal optimized according to the noise reduction parameter adjustment information with the plurality of loudness parameter models to obtain loudness comparison results respectively;

[0155] A loudness adjustment parameter calculation module, used to calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0156] The loudness optimization module is used to perform corresponding loudness adjustment on the audio segment of the digital audio signal optimized according to the noise reduction parameter adjustment information according to the loudness parameter adjustment information to obtain the digital audio signal optimized according to the loudness parameter adjustment information.

[0157] Fig.12 is a structural block diagram of an electronic device according to an embodiment of the present application. Fig.12As shown, the electronic device provided according to the embodiment of the present application includes: a sound pickup module, an attribute adjustment module, an original audio library, an adjusted audio temporary storage library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the original audio library is used to forward the digital audio signals to the comparison and analysis module, the comparison and analysis module is used to call at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare, analyze and optimize the digital audio signals to obtain parameter adjustment information and the digital audio signals optimized according to the parameter adjustment information, the adjusted audio library is used to send the digital audio signals optimized according to the parameter adjustment information to the speaker device, the attribute adjustment module is used to adjust the sound quality parameters of the sound pickup module according to the parameter adjustment information, and the speaker device is used to play back the digital audio signals optimized according to the parameter adjustment information. The electronic device can be various types of wireless microphones or wired microphones, and can communicate with the speaker device through a wired or wireless connection.

[0158] It is easy to understand that integrating the comparison and analysis module with the sound pickup module and the attribute adjustment module locally in the electronic device can greatly reduce the system scale, thereby saving software and hardware costs, while reducing the delay in adjusting the sound quality parameters and improving the real-time adjustment of the sound quality parameters.

[0159] In one embodiment, the attribute adjustment module includes an attribute parameter allocation module, an EQ adjustment module, a gain amplifier and a noise reduction module. The attribute parameter allocation module is used to allocate parameter adjustment information received by the signal transceiver module to the EQ adjustment module, the gain amplifier and the noise reduction module. The EQ adjustment module is used to adjust the EQ parameter of the digital audio signal according to the parameter adjustment information. The gain amplifier is used to adjust the loudness parameter of the digital audio signal according to the parameter adjustment information. The noise reduction module is used to adjust the noise reduction level of the digital audio signal according to the parameter adjustment information.

[0160] In one embodiment, the comparison and analysis module includes a timbre comparison and optimization module, a clarity comparison and optimization module and / or a loudness comparison and optimization module.

[0161] Furthermore, the timbre comparison and optimization module includes:

[0162] The timbre comparison module is used to retrieve multiple timbre reference models corresponding to different timbre modes from a large database, and compare and analyze the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result.

[0163] a timbre adjustment parameter calculation module, used to calculate the level difference corresponding to each frequency band of the digital audio signal as EQ parameter adjustment information according to the EQ comparison result; and

[0164] The timbre optimization module is used to perform EQ adjustment optimization of different timbre modes on the digital audio signal according to the EQ parameter adjustment information to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

[0165] Furthermore, the clarity comparison optimization module includes:

[0166] A clarity comparison module, used for retrieving multiple noise reduction reference models corresponding to the timbre mode from a large database, and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively;

[0167] A clarity adjustment parameter calculation module, used to calculate the noise reduction level required for the timbre mode according to the noise comparison result as noise reduction parameter adjustment information;

[0168] The timbre optimization module is used to perform noise reduction optimization in different timbre modes on the digital audio signal optimized according to the EQ parameter adjustment information to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

[0169] Furthermore, the loudness comparison optimization module includes:

[0170] A loudness comparison module, configured to retrieve a plurality of loudness parameter models corresponding to the noise reduction level and the timbre mode from a large database, and compare and analyze the digital audio signal optimized according to the noise reduction parameter adjustment information with the plurality of loudness parameter models to obtain loudness comparison results respectively;

[0171] A loudness adjustment parameter calculation module, used to calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result;

[0172] The loudness optimization module is used to perform corresponding loudness adjustment on the audio segment of the digital audio signal optimized according to the noise reduction parameter adjustment information according to the loudness parameter adjustment information to obtain the digital audio signal optimized according to the loudness parameter adjustment information.

[0173] According to a fourth aspect of an embodiment of the present application, a computer storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the audio adjustment method as described in the first aspect is implemented.

[0174] The audio adjustment device of this embodiment is used to implement the corresponding audio adjustment methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here. In addition, the functional implementation of each module in the audio adjustment device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be repeated here.

[0175] An embodiment of the present application also provides a computer program product, including computer instructions, which instruct a computing device to execute operations corresponding to any audio adjustment method in the above-mentioned multiple method embodiments.

[0176] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present application can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present application.

[0177] The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or implemented as software or computer code that can be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or implemented as a computer code originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded through a network and to be stored in a local recording medium, so that the method described herein can be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor or programmable or dedicated hardware (such as an AS IC or FPGA). It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, a processor or hardware, the audio adjustment method described herein is implemented. In addition, when a general-purpose computer accesses the code for implementing the audio adjustment method shown here, the execution of the code converts the general-purpose computer into a dedicated computer for executing the audio adjustment method shown here.

[0178] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present application.

[0179] The above implementation methods are only used to illustrate the embodiments of the present application, and are not limitations on the embodiments of the present application. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the embodiments of the present application. Therefore, all equivalent technical solutions also belong to the scope of the embodiments of the present application. The scope of patent protection of the embodiments of the present application should be limited by the claims.

Claims

1. An audio adjustment method, characterized in that: include: Collecting digital audio signals using a sound pickup device; Calling at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare, analyze and optimize the digital audio signal to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information; adjusting the sound quality parameter of the sound pickup device according to the parameter adjustment information; The digital audio signal optimized according to the parameter adjustment information is played back using a speaker device.

2. The audio adjustment method according to claim 1, characterized in that: The steps of analyzing and optimizing the digital audio signal by calling at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to obtain parameter adjustment information and optimizing the digital audio signal according to the parameter adjustment information include: The step of calling an EQ analysis and optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain EQ parameter adjustment information and a digital audio signal optimized according to the EQ parameter adjustment information; The step of calling a noise reduction analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain noise reduction parameter adjustment information and a digital audio signal optimized according to the noise reduction parameter adjustment information; and / or The step of calling a loudness analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain loudness parameter adjustment information and a digital audio signal optimized according to the loudness parameter adjustment information.

3. The audio adjustment method according to claim 2, characterized in that: The step of calling the EQ analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain EQ parameter adjustment information and optimizing the digital audio signal according to the EQ parameter adjustment information comprises: Retrieving multiple timbre benchmark models corresponding to different timbre modes from a large database; and comparing and analyzing the digital audio signal with the multiple timbre reference models respectively to obtain an EQ comparison result; Calculate the level difference corresponding to each frequency band of the digital audio signal according to the EQ comparison result as EQ parameter adjustment information; According to the EQ parameter adjustment information, EQ adjustment optimization of different timbre modes is performed on the digital audio signal to obtain a corresponding digital audio signal optimized according to the EQ parameter adjustment information.

4. The audio adjustment method according to claim 2, characterized in that: The step of calling the noise reduction analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain noise reduction parameter adjustment information and the step of optimizing the digital audio signal according to the noise reduction parameter adjustment information comprises: Retrieving multiple noise reduction benchmark models corresponding to the timbre mode from a large database; and comparing and analyzing the digital audio signal with the multiple noise reduction reference models respectively to obtain noise comparison results respectively; Calculate the noise reduction level required by the timbre mode according to the noise comparison result as noise reduction parameter adjustment information; The digital audio signal is subjected to noise reduction optimization in different timbre modes to obtain a digital audio signal optimized according to the noise reduction parameter adjustment information.

5. The audio adjustment method according to claim 2, characterized in that: The step of calling the loudness analysis optimization model according to at least one timbre mode to analyze and optimize the digital audio signal to obtain loudness parameter adjustment information and optimizing the digital audio signal according to the loudness parameter adjustment information comprises: Retrieving multiple loudness parameter models corresponding to the timbre mode from a large database; and comparing and analyzing the digital audio signal optimized according to the noise reduction parameter adjustment information with the multiple loudness parameter models to obtain loudness comparison results respectively; Calculate the loudness parameter adjustment information corresponding to the requirements of each audio segment according to the loudness comparison result; According to the loudness parameter adjustment information, corresponding loudness adjustment is performed on the audio segment of the digital audio signal to obtain a digital audio signal optimized according to the loudness parameter adjustment information.

6. The audio adjustment method according to claim 1, characterized in that: The method further comprises the following step: receiving mode instruction information input by a user.

7. The audio adjustment method according to claim 6, characterized in that: The step of adjusting the sound quality parameters of the sound pickup device according to the parameter adjustment information comprises: adjusting the sound quality parameters of the sound pickup device using the parameter adjustment information corresponding to the mode instruction information; and The step of using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information includes: using a speaker device to play back the digital audio signal optimized according to the parameter adjustment information corresponding to the mode instruction information.

8. The audio adjustment method according to claim 6, characterized in that: The artificial intelligence analysis model is retrieved from the big data model based on the pattern instruction information.

9. The audio adjustment method according to claim 6, characterized in that: The parameter adjustment information and the digital audio signal optimized by the parameter adjustment information are selected from a plurality of the parameter adjustment information and the digital audio signal optimized by the parameter adjustment information according to the mode instruction information.

10. An audio adjustment system, characterized in that: include: A server, a user terminal, a sound pickup device and a sound speaker, wherein the sound pickup device includes a signal transceiver module, a sound pickup module and an attribute adjustment module, the user terminal includes a first original audio library, a first attribute parameter temporary storage library and a first adjusted audio temporary storage library, the server includes a second attribute parameter temporary storage library, a second adjusted audio temporary storage library, an original audio library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the signal transceiver module is used to send the digital audio signals to the first original audio library, the first original audio library is used to forward the digital audio signals to the second original audio library of the server, and the comparison and analysis module is used to call at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare and analyze the digital audio signals. and optimization to obtain parameter adjustment information and a digital audio signal optimized according to the parameter adjustment information, the second adjustment audio temporary storage library is used to temporarily store the digital audio signal optimized according to the parameter adjustment information and forward it to the first adjustment audio temporary storage library, the second attribute parameter temporary storage library is used to temporarily store the parameter adjustment information and forward it to the first attribute parameter temporary storage library, the first adjustment audio temporary storage library is used to send the digital audio signal optimized according to the parameter adjustment information to a speaker device, the first attribute parameter temporary storage library is used to send the parameter adjustment information to the pickup device, the attribute adjustment module is used to adjust the sound quality parameters of the pickup module according to the parameter adjustment information, and the speaker device is used to play back the digital audio signal optimized according to the parameter adjustment information.

11. An electronic device, characterized in that: include: A sound pickup module, an attribute adjustment module, an original audio library, an adjusted audio temporary storage library and a comparison and analysis module, wherein the sound pickup module is used to collect digital audio signals, the original audio library is used to forward the digital audio signals to the comparison and analysis module, the comparison and analysis module is used to call at least one artificial intelligence analysis model of sound quality parameters according to at least one timbre mode to compare, analyze and optimize the digital audio signals to obtain parameter adjustment information and the digital audio signals optimized according to the parameter adjustment information, the adjusted audio temporary storage library is used to send the digital audio signals optimized according to the parameter adjustment information to a speaker device, the attribute adjustment module is used to adjust the sound quality parameters of the sound pickup module according to the parameter adjustment information, and the speaker device is used to play back the digital audio signals optimized according to the parameter adjustment information.

12. A computer storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the audio adjustment method according to any one of claims 1 to 9 is implemented.

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