Balanced control method and device for audio output, equipment and storage medium

Abstract

The invention relates to the technical field of audio processing, and discloses an audio output equalization control method and device, equipment and a storage medium, and the method comprises the steps: obtaining a current to-be-played audio signal, and recognizing the sound source type of the audio signal; determining a target tone quality and a target environment currently selected by the user; based on the sound source type and the target environment, using a room correction algorithm to calculate a sound effect equalization parameter matched with the target sound quality; and processing the audio signal based on the sound effect equalization parameter, and outputting and playing the audio signal through a corresponding audio device. In the application, the room correction equalization parameter and the user personality equalization parameter are determined through different sound source types and room correction algorithms, and the sound effect of the audio signal is comprehensively controlled, so that the sound effect is adjusted by independently setting the equalization parameter based on the sound source type, and the method does not depend on single EQ presetting any more, thereby adapting to sound effect consistent configuration of multiple scenes.

Description

Technical Field

[0001] The present application relates to the field of audio processing technology, and in particular to a method, device, equipment and storage medium for controlling audio output balance. Background Art

[0002] EQ (Equalizer) is an electronic device that can adjust the amount of signal amplification in each frequency band and is widely used in audio systems in various industries. However, current audio systems usually implement audio output processing by setting a fixed EQ. Such settings have the same equalization processing for audio from different sound sources.

[0003] With the diversified development of audio system usage scenarios, especially in home audio systems and professional music equipment, it summarizes usage scenarios such as movies, KTV and music appreciation. These usage scenarios are all generated in the same space and equipment. The sound sources corresponding to different usage scenarios have their own frequency requirements, and the current fixed EQ settings cannot adapt to such requirements, resulting in obvious differences in user experience of different sound sources in the same space. Summary of the invention

[0004] The present application provides an audio output balance control method, device, equipment and storage medium to solve the problem that the audio output processing of the audio system in the prior art cannot adapt to multiple scenes, resulting in inconsistent sound effects.

[0005] The first aspect of the present application provides a method for equalization control of audio output, the method comprising: obtaining an audio signal to be played currently, and identifying the sound source type of the audio signal; determining the target sound quality and target environment currently selected by the user; based on the sound source type and the target environment, using a room correction algorithm to calculate sound effect equalization parameters that match the target sound quality; processing the audio signal based on the sound effect equalization parameters, and outputting the audio signal for playback through a corresponding audio device.

[0006] In a feasible implementation manner, the obtaining of the audio signal to be played currently and identifying the sound source type of the audio signal includes: obtaining the audio signal to be played currently and analyzing the frequency spectrum characteristics of the audio signal; matching the frequency spectrum characteristics with the preset audio spectra of different sound sources to obtain the sound source type.

[0007] In a feasible implementation, the method of obtaining the audio signal to be played and identifying the sound source type of the audio signal includes: using an audio reading tool to collect the audio signal to be played to obtain a signal curve; using an audio analysis algorithm or an audio analysis tool to extract frequency band information of different time periods in the signal curve; and matching the energy intensity of each frequency band information with the energy grading of the preset audio spectra of different sound sources to obtain the sound source type.

[0008] In a feasible implementation, based on the sound source type and the target environment, the sound effect equalization parameters matching the target sound quality are calculated using a room correction algorithm, including: reading default equalization parameters based on the sound source type, wherein the equalization parameters include room correction equalization parameters and user personality equalization parameters; based on the target environment, environmental equalization parameters are calculated using a room correction algorithm, and the room correction equalization parameters in the equalization parameters are adjusted based on the environmental equalization parameters to obtain sound effect equalization parameters matching the target sound quality.

[0009] In a feasible implementation, after reading the default equalization parameters based on the sound source type, it also includes: loading a user interface for sound equalization control, wherein the user interface displays a room correction equalization parameter area and a user personality equalization parameter area; displaying the room correction equalization parameters and the user personality equalization parameters in corresponding areas, and constructing an adjustment progress bar corresponding to the user personality equalization parameters; in response to a sliding operation on the adjustment progress bar, determining the specific parameter values ​​of the user personality equalization parameters, and updating them.

[0010] In a feasible implementation, the audio signal is processed based on the sound effect equalization parameters and outputted and played through a corresponding audio device, including: merging the adjusted room correction equalization parameters and the user's personalized equalization parameters to obtain comprehensive sound effect equalization parameters; outputting the comprehensive sound effect equalization parameters to the audio device, and controlling the audio device to play the audio signal.

[0011] In a feasible implementation manner, the adjusted room correction equalization parameters and the user personality equalization parameters are combined to obtain comprehensive sound effect equalization parameters, including: calculating a frequency response curve for the adjusted room correction equalization parameters and the user personality equalization parameters respectively; and combining the two frequency response curves to obtain a comprehensive frequency response curve.

[0012] In a feasible implementation, after merging the two frequency response curves to obtain a comprehensive frequency response curve, the method further includes: fitting the comprehensive frequency response curve using a preset optimization algorithm to obtain a fitted frequency response curve, wherein the fitting is a deduplication operation.

[0013] In a feasible implementation, the audio signal is processed based on the sound effect equalization parameter and outputted for playback through a corresponding audio device, including: based on the adjusted room correction equalization parameter and the user personality equalization parameter, the audio signal is processed respectively and outputted for playback simultaneously through a corresponding audio device.

[0014] In a feasible implementation, the audio signal is processed based on the adjusted room correction equalization parameters and the user personalized equalization parameters, and is simultaneously output and played through corresponding audio devices, including: adjusting the audio signal based on the adjusted room correction equalization parameters to obtain corresponding room acoustic characteristics; based on the room acoustic characteristics, making a secondary adjustment to the audio signal using the adjusted user personalized equalization parameters to obtain personalized acoustic characteristics; and simultaneously outputting and playing through an audio device based on the room acoustic characteristics and the personalized acoustic characteristics.

[0015] In a feasible implementation manner, after the audio signal is processed based on the adjusted room correction equalization parameters and the user personality equalization parameters respectively, and outputted and played simultaneously through the corresponding audio device, it also includes: collecting real-time sound effect changes of the audio device during the process of playing the audio signal; comparing the sound effect changes with the sound effect equalization parameters to determine whether the two are consistent; if inconsistent, using a machine learning algorithm to record and learn the sound effect changes, and updating and storing the user personality equalization parameters based on the learning results.

[0016] The second aspect of the present application provides an audio output equalization control device, including: an acquisition module, used to acquire the audio signal currently to be played and identify the sound source type of the audio signal; a determination module, used to determine the target sound quality and target environment currently selected by the user; a calculation module, used to calculate the sound effect equalization parameters matching the target sound quality based on the sound source type and the target environment using a room correction algorithm; a processing module, used to process the audio signal based on the sound effect equalization parameters, and output and play it through a corresponding audio device.

[0017] The third aspect of the present application provides an audio device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the audio device executes the above-mentioned audio output equalization control method.

[0018] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned audio output equalization control method.

[0019] In the technical solution provided by the present application, the audio signal to be played is obtained, and the sound source type of the audio signal is identified; the target sound quality and target environment currently selected by the user are determined; based on the sound source type and the target environment, the sound effect equalization parameters that match the target sound quality are calculated using a room correction algorithm; the audio signal is processed based on the sound effect equalization parameters, and output and played through a corresponding audio device. In the present application, room correction equalization parameters and user personalized equalization parameters are determined through different sound source types and room correction algorithms, and the sound effects of the audio signal are comprehensively controlled, so as to achieve the adjustment of sound effects by individually setting equalization parameters based on the sound source type, and no longer rely on a single EQ preset, so as to adapt to the consistent configuration of sound effects in multiple scenes. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of an embodiment of a method for controlling the balance of audio output in an embodiment of the present application; Figure 2 A schematic diagram of another embodiment of the method for controlling the balance of audio output in the embodiment of the present application; Figure 3 A schematic diagram of an embodiment of a device for controlling the equalization of audio output in an embodiment of the present application; Figure 4 A schematic diagram of another embodiment of the audio output balance control device in the embodiment of the present application; Figure 5 This is a schematic diagram of an embodiment of an audio device in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present application provide a method, device, equipment and storage medium for audio output balance control, which matches the corresponding EQ configuration by identifying the audio source type, thereby realizing no longer relying on a single EQ preset; and after correcting the EQ in combination with the room correction algorithm, the audio device is controlled to play the audio, and the room correction algorithm can further optimize the sound quality in a variety of environments. Such a method can not only solve the problem of EQ settings not matching the sound source, but also enhance the consistency of audio performance, bringing a more convenient and efficient audio processing experience.

[0022] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] It is understandable that the execution subject of the present application can be an audio output balance control device, or a terminal or audio playback software or a server, which is not limited here. The embodiment of the present application is described by taking a server as an execution subject as an example. The server is a server in a local area network, and control software that can realize audio playback in multiple rooms is installed on the server, such as a certain music software.

[0024] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of the audio output balance control method in the embodiment of the present application includes: 101. Obtain an audio signal to be played currently, and identify a sound source type of the audio signal.

[0025] In this embodiment, when the server obtains the audio signal to be played, it can be the audio output by the server's own music software, or it can be the audio transmitted to the server when the user connects to the server's audio software / platform through a smart phone, IPAD or other device, where the audio format can be advanced multi-channel formats such as Dolby AC-3, DTS-HD, Dolby TrueHD or Atmos.

[0026] It is understandable that the server detects in real time whether the audio playback function is activated, for example, whether the audio playback software in the server is running. If so, the interface data output by each access interface of the audio playback software is collected, and the interface data containing audio data is extracted, and then the audio signal is parsed.

[0027] Specifically, by detecting the flag bit of each access interface, when the access interface is connected or accessed by other devices, the default value of the flag bit will be flipped, so as to determine the target access interface, read the interface data of the target access interface, and parse it to obtain the audio signal. When the audio signal is parsed, it is identified whether there is a data packet in the audio format in the parsed data. If so, the data packet is extracted and converted into an audio signal.

[0028] In actual applications, the audio signals output by different audio sources may be different. The difference may be in the audio signal format, the audio file suffix, or even the combination and sorting rules of the spectrum features.

[0029] By analyzing the spectral features in the audio signal and sorting the spectral features in chronological order, a spectral feature sequence is obtained; based on the sequence, the type of sound source is identified. It should be noted that the feature combination rules in audio of different sound source types are different. For example, the combination ratio of high and low tones in audio in movies and TV shows is different from that in pure music scenes. The same is true for different music types, including classical, pop, heavy bass, etc.

[0030] 102. Determine the target sound quality and target environment currently selected by the user.

[0031] The target sound quality and target environment are selected and customized by the user, and can be determined by identifying the touch operation of the user on the user interface of the music player software in the access server. Of course, the target sound quality can be automatically matched according to the target environment selected by the user, such as the target sound quality of room 1 is A sound quality, and the target sound quality of room 2 is B sound quality, etc.

[0032] 103. Based on the sound source type and target environment, the room correction algorithm is used to calculate the sound equalization parameters that match the target sound quality.

[0033] It should be noted that the sound effect equalization parameters include room correction equalization parameters and user personalized equalization parameters; firstly, the corresponding equalization parameter combination is matched by the sound source type, and the equalization parameter combination is a data group of room correction equalization parameters and user personalized equalization parameters; then, the parameters of the audio equipment and the parameters affecting the audio environment are determined based on the target environment; further, the room correction equalization parameters are generated based on the influencing parameters and the parameters of the equipment using the room correction algorithm. The user personalized equalization parameters are obtained by user customization after being matched based on the sound source type. The customization here can be a set of parameters generated in advance based on the user's preferences using a machine learning algorithm, or can be manually set by the user.

[0034] In this embodiment, after obtaining the room correction equalization parameters and the user personality equalization parameters, the sound effect equalization parameters can be formed by combination or merging, wherein the combination is to associate the two parameters in a set, and the merging is to generate a new equalization parameter based on the two parameters.

[0035] 104. Process the audio signal based on the sound effect equalization parameter, and output and play it through a corresponding audio device.

[0036] It should be noted that when using sound effect equalization parameters to process audio signals, it includes: using the equalization parameters obtained by combining the room correction equalization parameters and the user's personalized equalization parameters to process the audio signals and then play them, or using the room correction equalization parameters and the user's personalized equalization parameters to process the audio signals separately and then superimpose them for play.

[0037] In the embodiment of the present application, by identifying the audio source type and combining the room correction algorithm to determine the room correction equalization parameters and the user's personalized equalization parameters, and comprehensively controlling the sound effects of the audio signal, it is possible to adjust the sound effects by individually setting the equalization parameters based on the sound source type, and no longer rely on a single EQ preset, thereby adapting to the consistent configuration of sound effects in multiple scenarios, and significantly improving the coordination of audio playback and user experience.

[0038] See also Figure 2 Another embodiment of the audio output balance control method in the embodiment of the present application includes: 201. Obtain an audio signal to be played currently, and analyze frequency spectrum characteristics of the audio signal.

[0039] After receiving the audio signal to be played, the audio signal contains information of at least two channels; parsing the audio signal, identifying and separating the track information of each channel; pre-processing the separated track information of each channel according to a preset audio processing rule to obtain audio data containing multi-channel information.

[0040] Furthermore, the audio track information of each channel obtained by the analysis is subjected to spectrum analysis to obtain corresponding spectrum features, and finally the spectrum features of different channels at the same time are combined according to the time correspondence to obtain the spectrum features of the audio signal.

[0041] In another feasible implementation, when analyzing the frequency spectrum characteristics of an audio signal, an audio analysis algorithm may be used to analyze the frequency spectrum characteristics of an input sound source, such as using a Fourier transform method to analyze the audio signal.

[0042] 202. Match the frequency spectrum feature with the preset audio spectra of different sound sources to obtain the sound source type.

[0043] In this embodiment, the spectral features of the audio of different sound source types are defined in advance or extracted using a machine learning algorithm, and then the corresponding audio spectrum is constructed. The audio spectrum is actually the variation rule of the spectral features of the audio signal.

[0044] All the extracted spectral features are spliced ​​in chronological order to obtain a spectral feature sequence, and then the spectral feature sequence is matched and compared with the preset audio spectrum to automatically identify the type of sound source, such as music, movies, speech, etc. For example: if the energy of the high frequency band of the audio is strong, it may be pop music, while classical music is evenly distributed in low and high frequencies.

[0045] In another feasible implementation, when identifying the type of sound source, it can also be achieved by matching frequency band energy, specifically: The audio signal to be played is collected by an audio reading tool to obtain a signal curve; the frequency band information of different time periods in the signal curve is extracted by an audio analysis algorithm or an audio analysis tool; based on the energy intensity of each frequency band information, it is matched with the energy classification of the audio spectra of different preset sound sources to obtain the sound source type.

[0046] It should be noted that the audio signal to be played is obtained. Audio reading tools such as FFmpeg or Librosa are used to collect audio signals and generate signal curves. Subsequently, the frequency band information (i.e., spectrum features) of different time periods in the signal curve is extracted through audio analysis algorithms (such as short-time Fourier transform STFT) or audio analysis tools (such as Audacity). The energy intensity of the extracted frequency band information is matched with the energy grading of the audio spectra of different preset sound sources (such as human voice, instrument solo, symphony, etc.), thereby determining the sound source type of the current audio signal.

[0047] Among them, the short-time Fourier transform (STFT) is used to extract the spectral characteristics of the audio signal, and its extraction formula is:

[0048] Where x(n) is the audio signal, w(n) is the window function, R is the frame shift, and f is the frequency.

[0049] 203. Determine the target sound quality and target environment currently selected by the user.

[0050] 204. Read default equalization parameters based on the audio source type, where the equalization parameters include room correction equalization parameters and user personalized equalization parameters.

[0051] It is understandable that, with the audio source type as the search index, the corresponding equalization parameter settings are matched from the configuration table storing the audio source and the equalization parameter settings on the server, where it should be noted that the configuration table records the default setting parameters, which can be pre-set by the user according to personal preferences and environment. Specifically, the default setting parameters (i.e., the room correction equalization parameters PEQ and the user's personalized equalization parameters GEQ) are automatically loaded based on the audio source type.

[0052] For example: in classical music, the system automatically enhances low and high frequencies to highlight the clarity of musical instruments; if it is movie mode, the low frequencies are enhanced to highlight the sound effects.

[0053] 205. Based on the target environment, calculate the environment equalization parameters using the room correction algorithm, and adjust the room correction equalization parameters in the equalization parameters based on the environment equalization parameters to obtain the sound effect equalization parameters matching the target sound quality.

[0054] Specifically, the target environment is analyzed to obtain the room size, shape and material; then a geometric model of the room is constructed, and the room correction algorithm is used to perform acoustic simulation on the geometric model to obtain environmental equalization parameters; the environmental equalization parameters are combined with the default room equalization parameters for merged and fusion adjustment.

[0055] It is understandable that when the target environment is analyzed to obtain the room size, shape and material, the outline of the room is determined based on the target environment, and the measuring tools in the room are controlled to obtain the length, width, height and possible irregular shape area size of the room, and the three-dimensional size data of the room is recorded, expressed as L×W×H. Then the test audio is output, and the absorption capacity of the audio signal is evaluated according to the sound absorption coefficient α of the wall, floor, ceiling and other materials in the room, where the value range of the sound absorption coefficient α is 0 (complete reflection) to 1 (complete absorption).

[0056] Furthermore, a geometric model of the room is constructed, and the room correction algorithm is used to perform acoustic simulation on the geometric model to obtain the environmental balance parameters including: Use 3D modeling software (such as AutoCAD, SketchUp) to build a geometric model of the room based on the size and shape data. The geometric model should include the boundaries of the room (walls, floors, ceilings) and possible obstacles (such as furniture and columns). According to the material properties of the material obtained by analysis, the sound absorption coefficient α is assigned to each surface of the room, and the reflection coefficient R=1−α of the room is calculated based on the sound absorption coefficient α, where R represents the proportion of the audio signal reflected on the surface; The room transfer function H(f) is calculated using the Room Impulse Response (RIR). The room impulse response is measured by placing speakers and microphones in the room and playing and recording impulse signals. The frequency response of the room is then obtained by performing frequency domain analysis (such as Fast Fourier Transform, FFT) on these signals. The transfer function H(f) is expressed as a function of frequency f and reflects the frequency response characteristics of the room to the audio signal. It should be noted that the room transfer function is obtained from the room impulse response through Fast Fourier Transform (FFT), which describes the gain and phase of the room at each frequency.

[0057] The room mode theory is used to analyze the resonant frequency of the room; the formula for the resonant frequency fm is: , where n is the number of room modes, c is the speed of sound, V is the room volume, and A is the room surface area.

[0058] Based on the transfer function H(f) and the resonant frequency fm, the environmental equalization parameter E(f) is calculated; wherein the environmental equalization parameter E(f) is intended to compensate for the frequency response deviation of the room to the audio signal so that the audio signal is evenly distributed in the room. The formula of the environmental equalization parameter E(f) is E(f)=1 / |H(f)|, where |H(f)| is the modulus of the transfer function H(f).

[0059] The step of combining and adjusting the environment equalization parameters in combination with the default room equalization parameters includes: Merge the environment balance parameter E(f) and the default room balance parameter D(f), specifically, merge the calculated environment balance parameter E(f) and the default room balance parameter D(f) to obtain the adjusted room balance parameter A(f). The merging process is implemented by weighted averaging or interpolation method, for example: A(f)=βE(f)+(1−β)D(f), where β is a weight factor, ranging from 0 to 1; The adjusted room equalization parameter A(f) is optimized using an optimization algorithm (such as the least squares method, genetic algorithm) to reduce the fluctuation and distortion of the frequency response. It should be noted that the optimization goal of the optimization algorithm is to make the frequency response curve of A(f) as flat as possible, that is, the variation range of A(f) is minimized.

[0060] In this step, based on the characteristics of the target environment, the environment equalization parameters are calculated using the room correction algorithm, and based on these parameters, the room correction equalization parameters in the equalization parameters are adjusted to obtain sound equalization parameters that match the target sound quality, thereby optimizing the propagation effect of the audio signal in the room and improving the sound quality and auditory experience.

[0061] In another feasible implementation manner, after reading the default equalization parameters based on the sound source type, the method further includes: A user interface for sound equalization control is loaded, wherein the user interface displays a room correction equalization parameter area and a user personality equalization parameter area; the room correction equalization parameters and the user personality equalization parameters are displayed in corresponding areas, and an adjustment progress bar corresponding to the user personality equalization parameters is constructed; in response to a sliding operation on the adjustment progress bar, specific parameter values ​​of the user personality equalization parameters are determined and updated.

[0062] It is understandable that the music playback software of the server provides a user interface that allows users to manually adjust the gain of each frequency band to achieve the ideal sound effect. The adjustment can be reflected in the audio output in real time and saved as a personalized setting. For example, the user can choose to enhance the 40Hz low frequency part to highlight the bass effect, or reduce the 1kHz mid-frequency to reduce the noise in the audio.

[0063] 206. The adjusted room correction equalization parameters and the user personality equalization parameters are combined to obtain comprehensive sound effect equalization parameters.

[0064] Specifically, the adjusted room correction equalization parameters and the user personality equalization parameters are respectively used to calculate a frequency response curve; the two frequency response curves are combined to obtain a comprehensive frequency response curve.

[0065] By combining the frequency responses of PEQ and GEQ into a comprehensive frequency response, the final sound effect is balanced. For example, if PEQ mainly enhances the low frequency response, and GEQ enhances the high frequency, the final combination will present a smooth spectrum transition.

[0066] In practical applications, merging two frequency response curves into a comprehensive frequency response curve can be achieved through weighted averaging or interpolation. The formula for the weighted average is: H combined (f) = aH room (f)+(1−a)H user (f) Among them, H combined (f) is the comprehensive frequency response curve, H room (f) is the room correction frequency response curve, H user (f) is the user's individual frequency response curve, and a is the weight coefficient.

[0067] In another feasible implementation, after the two frequency response curves are combined to obtain a comprehensive frequency response curve, the method further includes: fitting the comprehensive frequency response curve using a preset optimization algorithm to obtain a fitted frequency response curve, wherein the fitting is a deduplication operation. It is understandable that the fitting can use the least squares method to optimize the calculation of the comprehensive frequency response curve, and the calculation formula is:

[0068] in, is the frequency response curve after fitting.

[0069] It is understood that the target response of the PEQ adjustment is set to be the ideal target to which the frequency response of the room is to be adjusted. For example, this target response can be a flat frequency response or a frequency response set according to certain acoustic standards.

[0070] The room transfer function and the target response are then compared at the same level, the differences between the two are calculated, and these differences are smoothed.

[0071] Finally, the frequency response curve generated by the PEQ parameters is fitted using a machine learning algorithm, and the optimized PEQ parameters are finally obtained to adjust the frequency response of the room to the target response. The fitting here refers to compressing and converting the frequency response curve generated by the PEQ parameters, that is, converting a curve composed of 20 PEQ parameters into a curve composed of 10 PEQ parameters, which can reduce duplicate parameters and improve system efficiency and sound quality. After fitting, the system only needs 10 parameters to achieve similar audio effects, thus achieving the purpose of using 10 parameters to represent 20 parameters and simplifying subsequent operations.

[0072] According to the optimized PEQ parameters (10-band PEQ, center frequency, gain, Q value), 10 cascaded biquad IIR filters are used to apply the PEQ parameters to the audio data in the time domain.

[0073] The filter coefficients (a1, a2, b0, b1, b2) for each band are calculated from the PEQ parameters (center frequency, gain, Q value). Use these coefficients to build a biquad IIR filter.

[0074] Apply these filters to the audio signal, and adjust the gain of the audio signal band by band in a cascaded manner to ultimately achieve the desired sound quality effect.

[0075] Furthermore, after obtaining the frequency response curve after fitting optimization, it also includes: detecting whether there is a user's preference setting or a custom working mode; if so, generating a new set of frequency response curves based on the preference setting or the EQ parameters in the custom working mode; based on a machine learning algorithm, using the PEQ parameters (10-band) after fitting optimization to fit this new set of frequency response curves to obtain the final PEQ parameters (10-band).

[0076] 207. Output to the audio device based on the comprehensive sound effect equalization parameter, and control the audio device to play the audio signal.

[0077] In this embodiment, in addition to adopting the above-mentioned merging method to obtain comprehensive sound effect equalization parameters, it can also be achieved by superposition, specifically: Based on the adjusted room correction equalization parameters and user personality equalization parameters, the audio signals are processed respectively, and output and played simultaneously through corresponding audio devices.

[0078] It is understandable that the audio signal is adjusted based on the adjusted room correction equalization parameters to obtain the corresponding room acoustic characteristics; based on the room acoustic characteristics, the audio signal is adjusted again using the adjusted user personalized equalization parameters to obtain personalized acoustic characteristics; based on the room acoustic characteristics and the personalized acoustic characteristics, the audio is output and played through the audio device at the same time. That is, by applying the PEQ parameters generated by the room correction algorithm, the audio is adjusted to adapt to the room acoustic characteristics. For example, in the low-frequency part where the room reflection frequency is strong, the system will reduce the gain of this frequency band.

[0079] On the basis of the room correction PEQ taking effect, the system superimposes GEQ parameters to achieve sound optimization for different sound sources. For example, in movie mode, GEQ enhances high frequencies to make the sound more penetrating, and combines with the room correction effect to achieve the best sound quality.

[0080] In another feasible implementation manner, after the audio signals are processed based on the adjusted room correction equalization parameters and the user personality equalization parameters, and are simultaneously output and played through corresponding audio devices, the method further includes: Collect the real-time sound effect changes of the audio device during the process of playing the audio signal; compare the sound effect changes with the sound effect equalization parameters to determine whether the two are consistent; if they are inconsistent, use a machine learning algorithm to record and learn the sound effect changes, and update and store the user's personalized equalization parameters based on the learning results.

[0081] It should be noted that when the audio device plays the audio signal, the system collects the sound effect changes in real time. This can be achieved by connecting a sound effect analysis device (such as an audio spectrum analyzer) to the output end of the audio device.

[0082] The collected sound effect changes are compared with the preset sound effect equalization parameters to determine whether the two are consistent. The comparison process can be achieved by calculating statistical indicators such as the mean square error (MSE) or correlation coefficient between the sound effect changes and the sound effect equalization parameters.

[0083] If the sound effect changes are inconsistent with the sound effect equalization parameters, the system uses machine learning algorithms (such as support vector machine SVM or neural network NN) to record and learn the sound effect changes. Based on the learning results, the system updates and stores the user's personalized equalization parameters so that the sound effect can be adjusted more accurately the next time the same type of audio signal is played.

[0084] In the embodiment of the present application, the audio signal to be played is obtained, and the source type of the audio signal is identified; the target sound quality and target environment currently selected by the user are determined; based on the source type and the target environment, the sound effect equalization parameters matching the target sound quality are calculated using the room correction algorithm; the audio signal is processed based on the sound effect equalization parameters, and the audio signal is output and played through the corresponding audio device. This implementation method solves the insufficiency of the prior art that it cannot flexibly adapt to different sound source types and room environments by independently configuring the audio processing method of EQ parameters combined with the room correction algorithm. Existing audio processing devices usually use fixed EQ presets, which cannot be personalized for different sound sources (such as music, movies, voice, etc.), and lack intelligent optimization mechanisms combined with room acoustic characteristics. In contrast, the technical solution introduces sound source recognition and dynamic EQ adjustment, so that the audio device can apply different EQ parameters for each sound source type, and further optimize the audio output in combination with the room correction algorithm, which greatly improves the flexibility and accuracy of audio processing. In addition, by providing the functions of manual adjustment by the user and automatic optimization by the system, the solution also enhances the user's sense of participation and personalized customization experience, which is a relatively rare innovation in the existing market.

[0085] The above describes the audio output balance control method in the embodiment of the present application. The following describes the audio output balance control device in the embodiment of the present application. Figure 3 In one embodiment of the present application, an audio output balance control device includes: The acquisition module 310 is used to acquire the audio signal to be played and identify the audio source type of the audio signal; A determination module 320, used to determine the target sound quality and target environment currently selected by the user; A calculation module 330, configured to calculate sound equalization parameters matching the target sound quality using a room correction algorithm based on the sound source type and the target environment; The processing module 340 is used to process the audio signal based on the sound effect equalization parameter, and output it for playback through a corresponding audio device.

[0086] In an embodiment of the present application, room correction equalization parameters and user personalized equalization parameters are determined by different sound source types and room correction algorithms, and the sound effects of the audio signal are comprehensively controlled to achieve the adjustment of sound effects by individually setting equalization parameters based on the sound source type, without relying on a single EQ preset, thereby adapting to consistent sound effect configuration in multiple scenarios.

[0087] See also Figure 4 Another embodiment of the audio output balance control device in the embodiment of the present application includes: The acquisition module 310 is used to acquire the audio signal to be played and identify the audio source type of the audio signal; A determination module 320, used to determine the target sound quality and target environment currently selected by the user; A calculation module 330, configured to calculate sound equalization parameters matching the target sound quality using a room correction algorithm based on the sound source type and the target environment; The processing module 340 is used to process the audio signal based on the sound effect equalization parameter, and output it for playback through a corresponding audio device.

[0088] Optionally, the acquisition module 310 includes: The analysis unit 311 is used to obtain the audio signal to be played and analyze the frequency spectrum characteristics of the audio signal; The first matching unit 312 is used to match the frequency spectrum feature with the preset audio spectra of different sound sources to obtain the sound source type.

[0089] Optionally, the acquisition module 310 further includes: The collecting unit 313 is used to collect the audio signal to be played by using an audio reading tool to obtain a signal curve; An extraction unit 314 is used to extract frequency band information of different time periods in the signal curve using an audio analysis algorithm or an audio analysis tool; The second matching unit 315 is configured to match the energy intensity of each frequency band information with the energy classification of the preset audio spectra of different sound sources to obtain the sound source type.

[0090] Optionally, the calculation module 330 includes: A reading unit 331 is used to read default equalization parameters based on the sound source type, wherein the equalization parameters include room correction equalization parameters and user personality equalization parameters; The calculation unit 332 is used to calculate the environmental equalization parameters based on the target environment using a room correction algorithm, and adjust the room correction equalization parameters in the equalization parameters based on the environmental equalization parameters to obtain the sound effect equalization parameters matching the target sound quality.

[0091] Optionally, the audio output balance control device further includes a display module 350, which is used to: Loading a user interface for sound effect equalization control, wherein the user interface displays a room correction equalization parameter area and a user personality equalization parameter area; Displaying the room correction equalization parameter and the user personality equalization parameter in corresponding areas, and constructing an adjustment progress bar corresponding to the user personality equalization parameter; In response to a sliding operation on the adjustment progress bar, a specific parameter value of the user personality balance parameter is determined and updated.

[0092] Optionally, the processing module 340 includes: A merging unit 341 is used to merge the adjusted room correction equalization parameters and the user personality equalization parameters to obtain a comprehensive sound effect equalization parameter; The playing unit 342 is used to output to the audio device based on the comprehensive sound effect equalization parameter, and control the audio device to play the audio signal.

[0093] Optionally, the merging unit 341 is specifically configured to: The adjusted room correction equalization parameters and the user's personalized equalization parameters are used to calculate a frequency response curve respectively; The two frequency response curves are combined to obtain a comprehensive frequency response curve.

[0094] Optionally, the processing module 340 further includes a fitting unit 343, configured to: The integrated frequency response curve is fitted using a preset optimization algorithm to obtain a fitted frequency response curve, wherein the fitting is a deduplication operation.

[0095] Optionally, the processing module 340 further includes: a superposition unit 344, configured to: Based on the adjusted room correction equalization parameters and user personality equalization parameters, the audio signals are processed respectively, and output and played simultaneously through corresponding audio devices.

[0096] Optionally, the superimposing unit 344 is specifically used for: Adjusting the audio signal based on the adjusted room correction equalization parameter to obtain corresponding room acoustic characteristics; Based on the room acoustic characteristics, the audio signal is adjusted again using the adjusted user personalized equalization parameter to obtain personalized acoustic characteristics; The audio is output and played simultaneously through an audio device based on the room acoustic characteristics and the individual acoustic characteristics.

[0097] Optionally, the audio output balance control device further includes a monitoring module 360, which is used to: Collecting real-time sound effect changes of the audio device during the process of playing the audio signal; Comparing the sound effect change with the sound effect equalization parameter to determine whether the two are consistent; If they are inconsistent, a machine learning algorithm is used to record and learn the sound effect changes, and the user personality equalization parameters are updated and stored based on the learning results.

[0098] In the embodiment of the present application, the corresponding EQ configuration is matched by identifying the audio source type, so as to achieve no longer relying on a single EQ preset; and after the EQ is corrected in combination with the room correction algorithm, the audio device is controlled to play the audio, and the room correction algorithm can further optimize the sound quality in a variety of environments. This method can not only solve the problem of EQ settings not matching the sound source, but also enhance the consistency of audio performance, bringing a more convenient and efficient audio processing experience.

[0099] above Figure 3 and Figure 4 The audio output balancing control device in the embodiment of the present application is described in detail from the perspective of modular functional entities, and the audio device in the embodiment of the present application is described in detail from the perspective of hardware processing.

[0100] See also Figure 5 As shown, the audio device includes a processor 500 and a memory 501 . The memory 501 stores machine executable instructions that can be executed by the processor 500 . The processor 500 executes the machine executable instructions to implement the above-mentioned audio output equalization control method.

[0101] Further, Figure 5 The audio device shown further includes a bus 502 and a communication interface 503 , and the processor 500 , the communication interface 503 and the memory 501 are connected via the bus 502 .

[0102] Among them, the memory 501 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), for example, at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 503 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 502 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0103] The processor 500 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 500. The above processor 500 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as a hardware decoding processor to be executed, or a combination of hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 501 , and the processor 500 reads the information in the memory 501 and completes the method steps of the above-mentioned embodiment in combination with its hardware.

[0104] The present application also provides an audio device, wherein the computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the audio output equalization control method in the above-mentioned embodiments.

[0105] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the audio output equalization control method.

[0106] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0108] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling audio output balance, characterized in that: The method comprises: Acquire the audio signal to be played and identify the audio source type of the audio signal; Determine the target sound quality and target environment currently selected by the user; Based on the sound source type and the target environment, a sound effect equalization parameter matching the target sound quality is calculated using a room correction algorithm, wherein the sound effect equalization parameter includes a room correction equalization parameter and a user personality equalization parameter; The audio signal is processed based on the sound effect equalization parameter, and is output and played through a corresponding audio device.

2. The audio output equalization control method according to claim 1, characterized in that: The step of obtaining the audio signal to be played and identifying the audio source type of the audio signal includes: Acquire the audio signal to be played, and analyze the frequency spectrum characteristics of the audio signal; The frequency spectrum feature is matched with the preset audio spectra of different sound sources to obtain the sound source type.

3. The audio output equalization control method according to claim 1, characterized in that: The step of obtaining the audio signal to be played and identifying the audio source type of the audio signal includes: Using an audio reading tool to collect the audio signal to be played, and obtaining a signal curve; Using an audio analysis algorithm or an audio analysis tool, extracting frequency band information of different time periods in the signal curve; Based on the energy intensity of each frequency band information, it is matched with the energy classification of the preset audio spectra of different sound sources to obtain the sound source type.

4. The audio output balance control method according to claim 1, characterized in that: The method of calculating the sound equalization parameters matching the target sound quality by using a room correction algorithm based on the sound source type and the target environment includes: Reading default equalization parameters based on the audio source type, wherein the equalization parameters include room correction equalization parameters and user personality equalization parameters; Based on the target environment, an environmental equalization parameter is calculated using a room correction algorithm, and the room correction equalization parameter in the equalization parameter is adjusted based on the environmental equalization parameter to obtain a sound effect equalization parameter that matches the target sound quality.

5. The audio output balance control method according to claim 4, characterized in that: After reading the default equalization parameters based on the sound source type, the method further includes: Loading a user interface for sound effect equalization control, wherein the user interface displays a room correction equalization parameter area and a user personality equalization parameter area; Displaying the room correction equalization parameter and the user personality equalization parameter in corresponding areas, and constructing an adjustment progress bar corresponding to the user personality equalization parameter; In response to a sliding operation on the adjustment progress bar, a specific parameter value of the user personality balance parameter is determined and updated.

6. The audio output balance control method according to claim 5, characterized in that: The processing of the audio signal based on the sound effect equalization parameter and outputting and playing the audio signal through a corresponding audio device includes: The adjusted room correction equalization parameters and the user's personalized equalization parameters are combined to obtain comprehensive sound effect equalization parameters; The audio signal is output to the audio device based on the comprehensive sound effect equalization parameter, and the audio device is controlled to play the audio signal.

7. The audio output balance control method according to claim 6, characterized in that: The adjusted room correction equalization parameters and the user personality equalization parameters are combined to obtain comprehensive sound effect equalization parameters, including: The adjusted room correction equalization parameters and the user's personalized equalization parameters are used to calculate a frequency response curve respectively; The two frequency response curves are combined to obtain a comprehensive frequency response curve.

8. The audio output balance control method according to claim 7, characterized in that: After the two frequency response curves are combined to obtain a comprehensive frequency response curve, the method further includes: The integrated frequency response curve is fitted using a preset optimization algorithm to obtain a fitted frequency response curve, wherein the fitting is a deduplication operation.

9. The audio output balance control method according to claim 5, characterized in that: The processing of the audio signal based on the sound effect equalization parameter and outputting and playing the audio signal through a corresponding audio device includes: Based on the adjusted room correction equalization parameters and user personality equalization parameters, the audio signals are processed respectively, and output and played simultaneously through corresponding audio devices.

10. The audio output balance control method according to claim 9, characterized in that: The audio signals are processed based on the adjusted room correction equalization parameters and the user personality equalization parameters, and are simultaneously output and played through corresponding audio devices, including: Adjusting the audio signal based on the adjusted room correction equalization parameter to obtain corresponding room acoustic characteristics; Based on the room acoustic characteristics, the audio signal is adjusted again using the adjusted user personalized equalization parameter to obtain personalized acoustic characteristics; The audio is output and played simultaneously through an audio device based on the room acoustic characteristics and the individual acoustic characteristics.

11. The audio output equalization control method according to any one of claims 1 to 10, characterized in that: After the audio signals are processed based on the adjusted room correction equalization parameters and the user personality equalization parameters, and are simultaneously output and played through corresponding audio devices, the method further includes: Collecting real-time sound effect changes of the audio device during the process of playing the audio signal; Comparing the sound effect change with the sound effect equalization parameter to determine whether the two are consistent; If they are inconsistent, a machine learning algorithm is used to record and learn the sound effect changes, and the user personality equalization parameters are updated and stored based on the learning results.

12. An audio output balance control device, characterized in that: The device comprises: An acquisition module, used to acquire the audio signal currently to be played and identify the sound source type of the audio signal; A determination module, used to determine the target sound quality and target environment currently selected by the user; A calculation module, configured to calculate, based on the sound source type and the target environment, sound effect equalization parameters matching the target sound quality using a room correction algorithm; The processing module is used to process the audio signal based on the sound effect equalization parameter and output it for playback through a corresponding audio device.

13. An audio device, characterized in that: The audio device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the audio device to execute the audio output equalization control method as described in any one of claims 1-11.

14. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the audio output equalization control method according to any one of claims 1 to 11 is implemented.

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